# Efference > Cameras and scheduled uplink for off-device inference and training. Efference builds Mono for the wrist, Stereo for the head, and Node for the multi-path uplink. These products support humans and robots, distributed data collection, and deployments using shared compute. The links below provide public site content in Markdown. Product pages are the source of current specifications; contact Efference for pricing and availability. Stereo is labeled December 2026. No unlisted price, certification, benchmark, or release date should be inferred. ## Products and company # Efference Canonical page: https://efference.ai/ Cameras and scheduled uplink for off-device inference and training. Explore Mono, Stereo, and Node for human and robotic data collection and deployments. Explore products Get in touch Mission To make robotic deployments scalable with shared compute. Today, on-device rules, but at an order of magnitude greater expense and difficulty to scale. We solve off-device, which doesn't work with today's technology. Our products Mono Designed for the wrist, for humans and robots. December 2026 Stereo Designed for the head, for humans and robots. Node Designed for the multi-path uplink, for uploads and deployments. Explore Mono Solutions Efference for Training We work with the data operators to deploy hardware and train foundation models at scale. Get in touch Efference for Deployments We work with robot companies to deploy networking and inference infrastructure so data center models can be deployed safely and with high performance. Get in touch Blog All posts Article A brain too big to carry Robot models, silicon efficiency, Jetson Thor vs. B300 TCO, deployments, and the network wall. September 14, 2026 Read on SemiAnalysis Help us build off-device Join us across perception, networking, and infrastructure to bring physical AI into the real world. Positions Wireless Wireless Systems Engineer, Access Points San Francisco · Full time · On-site Network Systems Engineer San Francisco · Full time · On-site Perception Image Quality Engineer, ISP Tuning San Francisco · Full time · On-site Computer Vision Engineer, VIO / SLAM San Francisco · Full time · On-site Robotics Robotics Researcher, Evaluations San Francisco · Full time · On-site Robotics Software Engineer, Infrastructure San Francisco · Full time · On-site View all open roles --- # Mono Canonical page: https://efference.ai/m1/ Mono is a 42 g camera designed for the wrist, for humans and robots. Explore standalone data collection, on-robot integration, imaging, and technical specifications. Designed for the wrist, for humans and robots. The mono is built for distributed data collection at scale, operating as a standalone device, and for direct deployments on-robot. ## Technical specifications - Dimensions: 51 × 42 × 32 mm (W × H × D) - Weight: 42 g - Interfaces: USB-C 3.0, Wi-Fi 6, Bluetooth 5 - Mounting Options: 1/4″-20 threaded mount on bottom; two M3 mounting points on back - Power: USB-C 3.0 (PoC) - Operating Temperature: −20 °C to 85 °C - Image Sensor: 1/2.6" in 2.3MP RGB - Pixel Size: 3.0 µm x 3.0 µm - Shutter: Electronically synchronized global shutter - Output Resolution: 1920x1200 @ 90, 60, 30, 15, 5, 1 fps (full resolution) 1920x1080 @ 120, 60, 30, 15, 5, 1 fps (cropping mode) 960x600 @ 120, 90, 60, 30, 15, 5, 1 fps (2x2 binning mode) - Dynamic Range: 65.5 dB - Sensitivity: 9606 mV/lux*s - Focal Length: 1.58 mm - Field of View: Max. 180° (H) x 120° (V) x 190° (D) - Aperture: f/2.1 - TV Distortion: < -30.80% - Construction: All Glass, Aluminum - CPU: Quad-core, up to 1.6 GHz - Memory: 1 GB - Storage: 64GB - NPU: 3.0 TOPS - Accelerometer Range: +/- 16G - Accelerometer Resolution: 0.48 mg - Accelerometer Noise Density: 4.0 mg - Gyroscope Range: +/- 1000 dps - Gyroscope Resolution: 0.04 mg - Gyroscope Noise Density: 0.08 dps - Output Data Rate: 840Hz - Wi-Fi: Wi-Fi 6 — IEEE 802.11a/b/g/n/ac/ax - Frequency bands: Dual-band 2.4 GHz and 5 GHz - Radio configuration: 1×1 (1T1R), single spatial stream - Channel bandwidth: 20 / 40 / 80 MHz - Maximum Wi-Fi data rate: Up to 600 Mbps PHY rate - Bluetooth: Bluetooth Classic (BR/EDR) and Bluetooth Low Energy (BLE) - Wi-Fi security: WPA / WPA2 / WPA3 Contact Efference for pricing and integration details: https://efference.ai/contact/ --- # Stereo Canonical page: https://efference.ai/h1/ Stereo is designed for the head, for humans and robots, with onboard localization and depth. Explore features, integration, and full technical specifications. Designed for the head, for humans and robots. The stereo is built for distributed data collection at scale, operating as a standalone device, and for direct deployments on-robot. Localization and depth computed with onboard compute. ## Technical specifications - Dimensions: 102 × 32 × 32 mm (W × H × D) - Baseline: 65mm - Weight: 95 g - Interfaces: USB-C 3.0, Wi-Fi 6, Bluetooth 5 - Mounting Options: 2x M4 threads (back; 75 mm VESA compatible), 1/4"-20 UNC threaded mount (bottom) - Power: USB-C 3.0 (PoC), M8 - Operating Temperature: −20 °C to 85 °C - Dual Image Sensors: 1/2.6" in 2.3MP RGB - Pixel Size: 3.0 µm x 3.0 µm - Shutter: Electronically synchronized global shutter, side by side - Output Resolution: 2x 1920x1200 @ 60, 30, 15, 5, 1 fps (full resolution) 2x 1920x1080 @ 60, 30, 15, 5, 1 fps (cropping mode) 2x 960x600 @ 120, 60, 30, 15, 5, 1 fps (2x2 binning mode) - Dynamic Range: 71.5 dB - Sensitivity: 9606 mV/lux*s - Focal Length: 2.5mm (0.1 in) - Field of View: Max. 100° (H) x 71° (V) x 112° (D) - Aperture: f/2.0 - TV Distortion: <-4% - Depth Range: 0.1m to 40m max; ideal range 0.5m to 20m - CPU: Quad-core, up to 1.6 GHz - Memory: 1 GB - Storage: 64GB - NPU: 3.0 TOPS - Accelerometer Range: +/- 16G - Accelerometer Resolution: 0.48 mg - Accelerometer Noise Density: 4.0 mg - Gyroscope Range: +/- 1000 dps - Gyroscope Resolution: 0.04 mg - Gyroscope Noise Density: 0.08 dps - Output Data Rate: 840Hz - Wi-Fi: Wi-Fi 6 — IEEE 802.11a/b/g/n/ac/ax - Frequency bands: Dual-band 2.4 GHz and 5 GHz - Radio configuration: 1×1 (1T1R), single spatial stream - Channel bandwidth: 20 / 40 / 80 MHz - Maximum Wi-Fi data rate: Up to 600 Mbps PHY rate - Bluetooth: Bluetooth Classic (BR/EDR) and Bluetooth Low Energy (BLE) - Wi-Fi security: WPA / WPA2 / WPA3 Contact Efference for pricing and integration details: https://efference.ai/contact/ --- # Node Canonical page: https://efference.ai/n1/ Node combines Wi-Fi 7 networking with 5G connectivity, connecting Mono and Stereo observation streams to shared compute for uploads and deployments. Designed for the multi-path uplink, for uploads and deployments. It combines Wi-Fi 7 networking with 5G connectivity. It connects Mono and Stereo observation streams to shared compute, from the home to the factory. ## Technical specifications - Processor: 64-bit ARM Cortex-A73 at 2.2 GHz - Memory: 1 GB DDR4 - Storage: 4 GB eMMC - OS: OpenWrt (Linux) - Standard: Wi-Fi 7; IEEE 802.11a/b/g/n/ac/ax/be - Bands & MIMO: 2.4, 5, and 6 GHz support; 2 × 2 MU-MIMO - Channel widths: 20, 40, 80, 160, and 320 MHz, depending on band and configuration - Peak PHY rates: Up to 688.2 Mbps at 2.4 GHz, 4.324 Gbps at 5 GHz, or 5.765 Gbps at 6 GHz. Per-band radio limits, not additive throughput. - Radio features: 4096-QAM and multi-link support; availability depends on firmware and client support - RF connections: 4 Wi-Fi antenna connections; 2 × 2 MIMO - 3GPP: Release 17; 5G NR SA / NSA, with LTE and WCDMA fallback - 5G SA, Sub-6 GHz: Up to 7.01 Gbps downlink / 1.25 Gbps uplink - 5G NSA, Sub-6 GHz: Up to 5.47 Gbps downlink / 730 Mbps uplink - 5G NSA, mmWave (optional): Up to 9.41 Gbps downlink / 3.66 Gbps uplink with mmWave antennas - Cellular MIMO: Sub-6 GHz: up to 4 × 4 downlink and 2 × 2 uplink on supported bands - LTE: Cat 20 downlink / Cat 18 uplink; up to 2 Gbps downlink / 211 Mbps uplink - WCDMA: Up to 42 Mbps downlink / 5.76 Mbps uplink; B1, B2, B4, B5, B8, B19 - 5G NR bands: n1, n2, n3, n5, n7, n8, n12, n13, n14, n18, n20, n25, n26, n28, n29 (receive only), n30, n38, n40, n41, n48, n53, n66, n70, n71, n75, n76, n77, n78, n79, n91, n92, n93, n94; mmWave n257, n258, n260, n261. Supported combinations depend on SA/NSA mode, firmware, antennas, and operator. - LTE bands: FDD: B1, B2, B3, B4, B5, B7, B8, B12, B13, B14, B17, B18, B19, B20, B25, B26, B28, B29, B30, B32, B66, B70, B71. TDD: B34, B38, B39, B40, B41, B42, B43, B48, B53. LAA: B46 (receive only). - SIM interfaces: 2 × (U)SIM interfaces, 1.8 / 3.0 V; optional eSIM - GNSS (optional): GPS, GLONASS, BeiDou, Galileo, and QZSS - Modem integration: USB 2.0 / 3.0 / 3.1 and single-lane PCIe; 3GPP TS 27.007 AT commands - Ethernet interfaces: 2 × USXGMII / 10GBase-R / SGMII+ / SGMII, plus 1 × USXGMII-M / PSGMII / QSGMII / SGMII+ / SGMII - External network ports: 1 × 10 GbE RJ45; 1 × 2.5 GbE RJ45; 1 × SFP port - USB: 1 × USB 3.0 - PCIe: PCIe 3.0; 2 × single-lane and 1 × dual-lane interfaces - Serial & I/O: UART, SPI, I²C, I²S, PWM, and 34 GPIOs - Networking supply: 3.3 V at the networking module; 12 W consumption - Modem supply: 3.135–4.4 V at the cellular module; 3.7 V typical - Power input: 12 / 24 V DC or USB-C Power Delivery; 48 V passive PoE on the 2.5 GbE port - Networking module: 38.3 × 61.7 mm; 20 g; solderable LGA - Cellular module: 52.0 × 30.0 × 2.3 mm; approximately 8.73 g; M.2 - Networking temperature: 0 to 65 °C - Modem temperature: Operating: −30 to 75 °C. Extended range: −40 to 85 °C; these are module ratings. Contact Efference for pricing and integration details: https://efference.ai/contact/ --- # Blog Canonical page: https://efference.ai/blog/ Read A brain too big to carry on SemiAnalysis: robot models, silicon efficiency, deployment costs, and the network wall. - [A brain too big to carry](https://newsletter.semianalysis.com/p/a-brain-too-big-to-carry-on-device): an article on SemiAnalysis. --- # Careers Canonical page: https://efference.ai/careers/ Explore open positions at Efference across perception, hardware, firmware, wireless, software, robotics, and growth and product. ## Open positions - [Solutions Engineer, Robotics](https://efference.ai/careers/robotics-solutions-engineer/): Growth & Product; San Francisco; Full time. - [Wireless Systems Engineer, Access Points](https://efference.ai/careers/wireless-systems-engineer-access-points/): Wireless; San Francisco; Full time. - [Wireless Systems Engineer, Client](https://efference.ai/careers/wireless-systems-engineer-client/): Wireless; San Francisco; Full time. - [RF Systems Engineer, Characterization & Validation](https://efference.ai/careers/wireless-systems-engineer-rf-test/): Wireless; San Francisco; Full time. - [UWB Systems Engineer](https://efference.ai/careers/uwb-engineer/): Wireless; San Francisco; Full time. - [Network Systems Engineer](https://efference.ai/careers/wireless-networking-engineer/): Wireless; San Francisco; Full time. - [Embedded Linux Engineer](https://efference.ai/careers/embedded-linux-engineer/): Firmware; San Francisco; Full time. - [Embedded Camera Engineer](https://efference.ai/careers/camera-embedded-software-engineer/): Firmware; San Francisco; Full time. - [Video Compression Engineer](https://efference.ai/careers/video-compression-engineer/): Firmware; San Francisco; Full time. - [Image Processing Engineer, Video Stabilization & Motion Estimation](https://efference.ai/careers/camera-algorithm-engineer-stabilization/): Perception; San Francisco; Full time. - [Image Processing Engineer, HDR & Tone Mapping](https://efference.ai/careers/research-engineer-hdr-video/): Perception; San Francisco; Full time. - [Image Quality Engineer, ISP Tuning](https://efference.ai/careers/camera-image-quality-tuning-engineer/): Perception; San Francisco; Full time. - [Image Processing Engineer, Testing & Automation](https://efference.ai/careers/camera-iq-test-software-engineer/): Perception; San Francisco; Full time. - [Optical Systems Engineer, Cameras](https://efference.ai/careers/camera-optical-engineer/): Perception; San Francisco; Full time. - [Computer Vision Engineer, VIO / SLAM](https://efference.ai/careers/research-engineer-vio-slam/): Perception; San Francisco; Full time. - [Computer Vision Engineer, Neural ISP & Depth](https://efference.ai/careers/research-engineer-neural-isp/): Perception; San Francisco; Full time. - [Electrical Engineer, PCB Design](https://efference.ai/careers/electrical-engineer-pcb/): Hardware; San Francisco; Full time. - [Product Design Engineer](https://efference.ai/careers/mechanical-engineer-robotics/): Hardware; San Francisco; Full time. - [Manufacturing and Process Engineer](https://efference.ai/careers/manufacturing-process-engineer/): Hardware; San Francisco; Full time. - [Robotics Researcher, Evaluations](https://efference.ai/careers/senior-rse-model-inference-evaluation/): Robotics; San Francisco; Full time. - [Robotics Researcher, Teleoperation](https://efference.ai/careers/senior-rse-teleoperation/): Robotics; San Francisco; Full time. - [Robotics Software Engineer, Controls](https://efference.ai/careers/senior-rse-controls/): Robotics; San Francisco; Full time. - [Robotics Software Engineer, Infrastructure](https://efference.ai/careers/rse-infrastructure/): Robotics; San Francisco; Full time. - [Machine Learning Infrastructure Engineer, Orchestration](https://efference.ai/careers/ml-infrastructure-engineer-cluster-orchestration/): Software; San Francisco; Full time. - [Machine Learning Infrastructure Engineer, Kernel Optimization](https://efference.ai/careers/ml-infrastructure-engineer-gpu-systems/): Software; San Francisco; Full time. - [Software Engineer, Full-Stack](https://efference.ai/careers/software-engineer-full-stack/): Software; San Francisco; Full time. - [Software Engineer, SDKs](https://efference.ai/careers/software-engineer-sdks/): Software; San Francisco; Full time. - [Product, Design](https://efference.ai/careers/product-designer-software/): Growth & Product; San Francisco; Full time. - [Growth & Partnerships Lead](https://efference.ai/careers/growth-marketing-lead/): Growth & Product; San Francisco; Full time. - [Chief of Staff](https://efference.ai/careers/chief-of-staff/): Growth & Product; San Francisco; Full time. - [Technical Buyer, Electronics & Hardware](https://efference.ai/careers/technical-buyer-electronics-hardware/): Hardware; San Francisco; Full time. - [Supply Chain Operations & Trade Compliance Lead](https://efference.ai/careers/supply-chain-operations-trade-compliance-lead/): Hardware; San Francisco; Full time. - [Systems Test Engineer, End-to-End Validation](https://efference.ai/careers/systems-test-engineer-end-to-end-validation/): Software; San Francisco; Full time. - [Hardware Test Engineer, Reliability & Manufacturing](https://efference.ai/careers/hardware-test-engineer-reliability-manufacturing/): Hardware; San Francisco; Full time. --- # Contact and location Canonical page: https://efference.ai/contact/ Contact Efference about Mono, Stereo, Node, training, or deployments. Find our team in North Beach, San Francisco, and get in touch. Contact Let’s talk off-device. For pricing, availability, technical documentation, or investor inquiries, we’d love to hear from you. Phone +61 432 678 884 Our location North Beach, San Francisco, CA 94133 USA Email team@efference.ai Social network Get in touch Tell us what you’re building and how we can help. Full name Email Message Send message Thank you. Your message has been sent. North Beach, San Francisco Open map --- # Terms and conditions Canonical page: https://efference.ai/terms/ Terms for the Efference website, product orders, software, integration, and related services. Legal Terms & Conditions Last updated October 17, 2026 01 Scope and acceptance 02 Orders, pricing, and payment 03 Delivery and product information 04 Robotics integration and safe use 05 Software, firmware, and documentation 06 Networks and third-party services 07 Data and privacy 08 Warranties, returns, and support 09 Intellectual property and acceptable use 10 Disclaimers and limitations of liability 11 Access, suspension, and termination 12 Governing law and disputes 13 Changes to these terms 14 Contact 01 Scope and acceptance These Terms & Conditions govern access to Efference’s website and, when incorporated into an accepted order or agreement, the purchase or use of our hardware, firmware, software, documentation, and related services. “Efference,” “we,” and “us” refer to the business operating this website and identified in your applicable order or agreement. “You” means the person or organization using the website or acquiring our products. By using the website, you agree to these terms to the extent permitted by law. If you act for an organization, you represent that you have authority to bind it. A signed agreement, accepted order, product-specific license, or written warranty controls if it conflicts with these terms on the same subject. Mandatory legal rights remain unaffected. 02 Orders, pricing, and payment Website listings, demonstrations, and pricing discussions are invitations to inquire, not an obligation to supply. An order becomes binding when Efference accepts it in writing. The accepted order sets out the products, quantities, prices, payment schedule, and any taxes, shipping charges, or other fees. You must provide accurate billing and delivery information and pay undisputed amounts when due. Changes and cancellations require written agreement, except where applicable law provides otherwise. We will communicate any proposed substitution or material change to an accepted order rather than treating updated website information as a change to that order. 03 Delivery and product information Delivery estimates are not guarantees unless expressly agreed in writing. Shipping terms, transfer of title, and risk of loss are governed by the accepted order and applicable law. Please notify us promptly of missing items or visible transit damage so we can help resolve the issue. Specifications and availability may change for future products or orders. Illustrations, simulations, benchmarks, and demonstrations show particular configurations or test conditions; actual performance depends on the complete system and operating environment. Specifications expressly agreed for an accepted order remain subject to that agreement. Evaluation or preproduction units will be identified as such and may have separate evaluation terms. 04 Robotics integration and safe use You are responsible for evaluating product suitability for your application, following the applicable installation and operating documentation, and validating the complete robot or system before deployment. Use appropriate electrical, thermal, mechanical, network, and cybersecurity safeguards, including safe fallback behavior when connectivity, power, sensing, or inference fails. Do not assume that a camera, networking device, software component, or model output is a certified safety function. Safety-related use requires the relevant documented capabilities and system-level validation. Maintain appropriate human oversight, emergency stops, access controls, and operating procedures for your application. These responsibilities do not limit Efference’s obligations or liability that cannot lawfully be limited. 05 Software, firmware, and documentation Unless a separate license applies, Efference grants you a limited, non-exclusive license to use the software, firmware, and documentation supplied with a lawfully acquired product for its intended operation and integration. Ownership of intellectual property does not transfer with the hardware. You may not unlawfully copy, distribute, sublicense, bypass access controls, or reverse engineer proprietary software, except where permitted by applicable law. Open-source and third-party components remain subject to their own licenses, which control for those components. Updates, support periods, hosted features, and service commitments are provided only as described in the applicable agreement or product documentation. 06 Networks and third-party services Wireless performance, synchronization, latency, throughput, and inference results depend on factors including configuration, interference, network capacity, model behavior, and third-party infrastructure. You are responsible for obtaining necessary connectivity, credentials, subscriptions, and permissions unless your agreement provides otherwise. Third-party websites, platforms, software, and services have their own terms. Links on our website do not create an endorsement or make Efference responsible for third-party content. Any guaranteed service levels or performance commitments must be stated in your written agreement. 07 Data and privacy You retain your rights in the images, sensor observations, recordings, and other data you collect or supply. These terms do not transfer ownership of that data to Efference or grant a general right to use it for model training. Any processing by Efference for a hosted service, support engagement, or data project must follow the applicable agreement and the privacy information provided for that activity. You are responsible for having the rights, notices, permissions, and safeguards required for your collection and use of data, including recordings of people or private spaces. Protect credentials and confidential information, maintain appropriate backups, and avoid submitting sensitive data through ordinary website contact forms. 08 Warranties, returns, and support Any product warranty, service commitment, return eligibility, or repair process is described in the written terms supplied for the relevant product or order, together with applicable law. This page does not create a separate warranty period or reduce an express warranty. 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You must follow applicable export controls, sanctions, radio-frequency rules, and other laws relevant to your purchase, integration, and use. 10 Disclaimers and limitations of liability To the extent permitted by law, the website and general informational materials are provided “as is” and “as available,” without a promise that they will be uninterrupted or error-free. This disclaimer does not override product warranties, specifications agreed in writing, or non-waivable legal rights. To the extent permitted by law and unless a written agreement provides otherwise, neither party is liable to the other for indirect or consequential loss, including lost profits or business interruption, arising from these terms. For business customers, Efference’s aggregate liability for a claim relating to a product or service is limited to the amount paid or payable for the affected product or service during the twelve months preceding the event giving rise to the claim. These exclusions and limits do not apply to fraud, willful misconduct, gross negligence, death or personal injury where liability cannot be limited, or any other liability or remedy that applicable law does not allow the parties to exclude or limit. They do not reduce mandatory consumer rights. 11 Access, suspension, and termination We may restrict access to the website or a service to address unlawful activity, security risks, or a material breach of applicable terms. Where reasonably practicable, we will provide notice and an opportunity to resolve the issue. Paid services and product licenses remain governed by their applicable agreements; these website terms do not create a general right to disable purchased hardware. Terms that by their nature should survive termination, including accrued payment obligations, intellectual property provisions, and lawful liability limitations, continue to apply. 12 Governing law and disputes Unless your written agreement or mandatory law provides otherwise, these terms are governed by California law, excluding its conflict-of-law rules. The state and federal courts located in San Francisco, California will have jurisdiction over disputes arising from these terms. This does not deprive consumers of protections or access to courts required by the law that applies to them. Please contact us first so we can try to resolve a concern directly. This request does not prevent you from seeking urgent relief or exercising a legal right. If a provision is unenforceable, the remaining provisions remain effective to the extent permitted by law. 13 Changes to these terms We may update these terms by posting a revised version and updating the date shown above. Changes apply prospectively. They do not retroactively alter accepted orders, existing warranties, or signed agreements without the agreement or notice required by those documents and applicable law. 14 Contact For questions about these terms, orders, or product support, email team@efference.ai . Efference North Beach, San Francisco, CA 94133 USA Please contact us for shipping or return instructions before sending physical items. --- # Solutions Engineer, Robotics Canonical page: https://efference.ai/careers/robotics-solutions-engineer/ Solutions Engineer, Robotics at Efference. San Francisco · Full time · On-site. You'll help robotics teams integrate Efference into their systems and make those deployments work in practice. You'll help robotics teams integrate Efference into their systems and make those deployments work in practice. Your time will be split roughly evenly between hands-on SDK and robotics development and customer conversations, technical evaluations, and troubleshooting. ## What you’ll do - Work with customers to understand their robot architecture, sensor streams, inference requirements, and deployment constraints; turn those conversations into an integration plan. - Write SDK features, robot adapters, examples, and diagnostic tools that help customers get from their first camera stream to a working deployment. - Reproduce customer problems on our hardware, trace failures across the camera, network, and inference stack, and implement fixes with the relevant engineers. - Run technical demonstrations and evaluations with the growth team, agreeing on measurable success criteria and explaining performance and cost tradeoffs clearly. - Own the technical relationship through onboarding and ongoing use, keeping customers informed and following unresolved issues through to completion. - Bring recurring customer needs into engineering planning, recommend priorities, and help teammates become more effective at explaining and supporting the product. ## What we are looking for - Experience integrating or deploying robotic systems, with enough depth to debug sensor, middleware, and application behavior on Linux. - Strong Python or C++ skills and a record of contributing code that other engineers use and maintain. - Comfort discussing camera pipelines, networking, and model inference with technical customers, including areas where you need to investigate before answering. - An ability to ask useful questions, listen carefully, and explain a technical problem without losing the person you're speaking to. - Reliable follow-through, openness to feedback, and sound judgment about which customer problems need an immediate fix or a product change. ## Nice to Have - Experience with ROS 2, NVIDIA Jetson, robot learning frameworks, or remote inference. - Previous work in solutions engineering, developer support, or technical account management. - Experience guiding a hardware or infrastructure evaluation through to a production deployment. --- # Wireless Systems Engineer, Access Points Canonical page: https://efference.ai/careers/wireless-systems-engineer-access-points/ Wireless Systems Engineer, Access Points at Efference. San Francisco · Full time · On-site. You'll build access points and coordinated wireless networks for robots that continuously send sensor data to shared compute over multiple paths. You'll build access points and coordinated wireless networks for robots that continuously send sensor data to shared compute over multiple paths. The work spans radio platform selection, firmware and driver development, and uplink scheduling that keeps observations moving as robots, interference, and fleet load change. ## What you’ll do - Define the access point architecture with electrical and RF engineers, select radio platforms, and bring up custom hardware from early boards through deployment. - Develop MAC, firmware, and driver features for uplink scheduling, traffic prioritization, admission control, and airtime allocation across multiple robots. - Build coordination between access points for handoffs, channel selection, and mesh or wired backhaul; measure the airtime cost and resilience of each topology. - Develop beamforming, rate adaptation, and traffic distribution across radio links; evaluate MIMO and multi-path performance under obstruction, motion, and competing traffic. - Work with client, UWB, and embedded engineers on clock distribution and location-assisted scheduling, with explicit limits for synchronization error and handoff interruption. - Instrument queues, retransmissions, channel use, and observation delivery; reproduce field failures and improve tail latency and delivery rate under realistic load. ## What we are looking for - Experience developing Wi-Fi access points, wireless firmware, MAC algorithms, or comparable radio systems beyond network configuration. - Strong understanding of 802.11 channel access, aggregation, retransmission, QoS, beamforming, mesh networks, and handoffs. - Proficiency in C or C++ and hands-on work with embedded Linux, wireless drivers, or radio firmware. - Experience bringing up hardware and using packet captures, firmware traces, and RF measurements to explain wireless failures. - Ability to turn latency, capacity, and reliability requirements into experiments and implementation decisions. ## Nice to Have - Experience with Wi-Fi 6/7, uplink OFDMA or MU-MIMO, multi-link operation, or coordinated access points. - Work with hostapd, mac80211/cfg80211, vendor wireless SDKs, or programmable radio platforms. - Experience with industrial wireless deployments, timing protocols, or moving clients in dense multipath environments. - Experience with 5G radio access or private cellular networks, including integration with Wi-Fi in multi-path systems. --- # Wireless Systems Engineer, Client Canonical page: https://efference.ai/careers/wireless-systems-engineer-client/ Wireless Systems Engineer, Client at Efference. San Francisco · Full time · On-site. You'll build the wireless software that connects Efference devices and customer robot computers to our access points. You'll build the wireless software that connects Efference devices and customer robot computers to our access points. You'll work from radio firmware and Linux drivers up through the host data path, making high-rate sensor uplinks reliable on platforms such as NVIDIA Jetson and our own hardware. ## What you’ll do - Integrate wireless chipsets on customer and Efference platforms, including driver porting, firmware configuration, board bring-up, and interface validation. - Implement the client side of our access point scheduling and timing protocols, coordinating transmission with observation capture and application deadlines. - Tune transmit queues, aggregation, retransmissions, interrupt handling, and host-to-radio transfers to reduce latency without sacrificing useful throughput. - Integrate beamforming feedback and handoffs across mesh access points, preserving sessions as traffic moves between radio links in a multi-path system. - Expose link quality and queue information to compression and robotics software so applications can adapt before observations become stale. - Build repeatable interoperability and stress tests across firmware, kernel, chipset, and host-platform versions; investigate failures using traces from both ends of the link. ## What we are looking for - Experience writing or modifying wireless device drivers, radio firmware, or low-level networking software on embedded platforms. - Strong C/C++ skills and understanding of concurrency, DMA, interrupt handling, and memory ownership across hardware and software. - Working knowledge of Wi-Fi channel access, QoS, power saving, rate control, beamforming, mesh networks, and handoffs. - Ability to debug Linux networking with packet captures, kernel tracing, driver logs, and hardware instrumentation. - Experience resolving integration issues across a hardware vendor's software stack and a production operating system. ## Nice to Have - Experience with Jetson, ARM Linux, PCIe/SDIO radios, or custom board support packages. - Knowledge of mac80211, cfg80211, wpa_supplicant, or vendor Wi-Fi driver architectures. - Experience with hardware timestamping, Wi-Fi multi-link operation, cellular fallback, or latency-sensitive video transport. --- # RF Systems Engineer, Characterization & Validation Canonical page: https://efference.ai/careers/wireless-systems-engineer-rf-test/ RF Systems Engineer, Characterization & Validation at Efference. San Francisco · Full time · On-site. You'll develop and characterize the RF and antenna systems that keep moving robots connected to Efference infrastructure. You'll develop and characterize the RF and antenna systems that keep moving robots connected to Efference infrastructure. You'll connect antenna and radio measurements to application performance, identifying how robot geometry, electronics, and the surrounding environment affect the link. ## What you’ll do - Design, prototype, and tune antennas and matching networks with electrical engineers and the product design team, accounting for enclosure materials, mounting, and robot orientation. - Characterize antenna patterns, beamforming performance, efficiency, isolation, transmit quality, and receiver sensitivity through conducted and over-the-air measurements. - Investigate desense and interference from compute, power electronics, cameras, cables, motors, and neighboring radios; verify fixes on assembled systems. - Develop repeatable tests for multipath, blockage, polarization changes, and motion in mesh networks; correlate RF measurements with packet loss and latency during handoffs. - Build automated measurement tools, calibration procedures, and uncertainty checks so results remain comparable across prototypes, labs, and suppliers. - Support site surveys, antenna placement, RF production limits, and radio certification testing; document failure mechanisms and design changes with measured evidence. ## What we are looking for - Hands-on experience developing or validating antennas and RF systems for wireless products. - Strong understanding of electromagnetic propagation, impedance matching, link budgets, receiver impairments, and interference mechanisms. - Experience with vector network analyzers, spectrum analyzers, signal generators, and conducted or radiated test setups. - Ability to connect EVM, sensitivity, antenna patterns, and beamforming measurements to link reliability and handoff performance. - Python or comparable automation skills, careful measurement practice, and experience debugging across RF, electrical, and mechanical boundaries. ## Nice to Have - Antenna simulation experience with HFSS, CST, or similar tools, including MIMO antenna systems. - Work on Wi-Fi, UWB, industrial radios, or wireless products mounted near metal and moving machinery. - Experience with chamber testing, regulatory test labs, RF calibration, or production correlation. --- # UWB Systems Engineer Canonical page: https://efference.ai/careers/uwb-engineer/ UWB Systems Engineer at Efference. San Francisco · Full time · On-site. You'll build UWB localization for robot fleets operating in instrumented environments. You'll build UWB localization for robot fleets operating in instrumented environments. You'll develop the ranging, timing, and estimation stack, then use position information to support beamforming, mesh coordination, and handoffs across access points. ## What you’ll do - Define anchor and tag architectures, ranging protocols, update rates, and fleet capacity against the accuracy and coverage requirements of each site. - Implement and compare two-way ranging and time-difference-of-arrival approaches, including anchor synchronization and antenna-delay calibration. - Develop localization and tracking algorithms that expose uncertainty and handle non-line-of-sight bias, multipath, missed measurements, and moving obstructions. - Bring up UWB hardware and firmware with the electrical and embedded teams, validating timestamp behavior from the radio through the host interface. - Provide calibrated position and motion estimates for beamforming and handoff decisions in mesh networks; validate gains against measured channel conditions. - Build ground-truth experiments, site calibration tools, and fleet-scale tests covering positioning error, update latency, outage duration, and recovery. ## What we are looking for - Experience developing UWB ranging, indoor localization, radio sensing, or a closely related positioning system. - Strong understanding of time-of-flight measurement, clock error, estimation, and the effects of propagation on ranging accuracy. - Proficiency in C/C++ and Python or MATLAB for embedded implementation, modeling, and data analysis. - Hands-on experience bringing up radios and debugging hardware, firmware, protocol, and measurement issues together. - Ability to design controlled experiments and distinguish a calibration problem from a limitation of the environment or measurement geometry. ## Nice to Have - Experience with IEEE 802.15.4z, FiRa protocols, or commercial UWB chipsets. - Work with angle-of-arrival estimation, channel impulse responses, or sensor fusion with IMUs and visual odometry. - Experience surveying anchors and deploying localization systems in factories, warehouses, or other obstructed spaces. --- # Network Systems Engineer Canonical page: https://efference.ai/careers/wireless-networking-engineer/ Network Systems Engineer at Efference. San Francisco · Full time · On-site. You'll own the multi-path network between our access points and the compute that serves robot models. You'll own the multi-path network between our access points and the compute that serves robot models. You'll make sensor uploads and returning inference results fast and predictable, working with wireless, robotics, and ML infrastructure engineers to control queueing and recover from failures. ## What you’ll do - Design and implement multi-path transport across mesh backhaul, site uplinks, and datacenter hosts, with explicit budgets for latency, jitter, loss, and observation age. - Develop traffic classification, pacing, congestion control, and backpressure that protect live inference and control traffic when recordings or other workloads compete for bandwidth. - Tune Linux network paths and NIC behavior, profiling socket buffers, packet processing, CPU affinity, copies, and application-level queueing. - Build connection establishment, authentication, reconnect, and failover behavior that preserves sessions through handoffs, changing routes, and customer firewalls. - Implement cross-host timing and tracing with embedded engineers, separating clock uncertainty from actual transport delay. - Test multi-path routing, mesh failures, beamforming changes, and handoffs with wireless engineers; measure loss, reordering, and latency under concurrent robot traffic. ## What we are looking for - Experience building production networking software or distributed systems where latency and availability matter. - Deep understanding of TCP/IP, UDP, routing, queueing, congestion, and how transport choices affect application behavior. - Strong systems programming in C++, Rust, or Go, plus practical Linux networking and performance debugging skills. - Experience measuring tail latency and diagnosing problems using packet traces, host instrumentation, and realistic load tests. - Ability to reason across application, operating system, network equipment, and provider boundaries. ## Nice to Have - Experience with WebRTC, QUIC, real-time media, or custom transport for sensor data. - Knowledge of PTP, hardware timestamping, eBPF/XDP, DPDK, RDMA, or accelerated NIC paths. - Experience with robotics, edge-to-cloud infrastructure, or deploying services on customer-controlled networks. --- # Embedded Linux Engineer Canonical page: https://efference.ai/careers/embedded-linux-engineer/ Embedded Linux Engineer at Efference. San Francisco · Full time · On-site. You'll own the Linux platform that brings Efference hardware to life and keeps it running in the field. You'll own the Linux platform that brings Efference hardware to life and keeps it running in the field. Your work will give camera, wireless, and perception engineers a dependable base for building low-latency systems on custom boards. ## What you’ll do - Bring up new hardware from bootloader and board support package through kernel, device trees, peripheral drivers, and system services. - Build reproducible operating system images and cross-compilation toolchains, maintaining a clear path from development builds to released firmware. - Integrate camera, network, IMU, and accelerator subsystems with their owners; resolve memory, interrupt, power, and bus-level conflicts. - Implement platform support for hardware timestamps, clock synchronization, and scheduling, measuring behavior under combined camera, radio, and compute load. - Develop secure boot and signed update support, recovery paths, watchdogs, and useful device diagnostics with the fleet and SDK teams. - Debug kernel crashes, boot failures, resource leaks, and thermal or power-related behavior; turn fixes into automated board and release checks. ## What we are looking for - Experience shipping embedded Linux products, including board bring-up, kernel development, or substantial BSP ownership. - Strong C/C++ skills and knowledge of Linux memory management, concurrency, device models, and userspace interfaces. - Experience with bootloaders, device trees, cross-compilation, and build systems such as Yocto or Buildroot. - Ability to read schematics and datasheets and use serial consoles, JTAG, oscilloscopes, or logic analyzers during debugging. - A record of diagnosing failures across hardware and software and maintaining platform changes through production releases. ## Nice to Have - Experience with ARM SoCs, Jetson, PCIe, MIPI interfaces, or heterogeneous CPU/NPU platforms. - Work on PREEMPT_RT, PTP, DMA-BUF, zero-copy pipelines, or Linux performance tracing. - Experience with fleet updates, device security, manufacturing provisioning, or upstream Linux contributions. --- # Embedded Camera Engineer Canonical page: https://efference.ai/careers/camera-embedded-software-engineer/ Embedded Camera Engineer at Efference. San Francisco · Full time · On-site. You'll own camera bring-up and the low-level software that turns sensor output into reliable, correctly timed frames. You'll own camera bring-up and the low-level software that turns sensor output into reliable, correctly timed frames. You'll work with electrical, embedded Linux, and imaging engineers to support new sensors and maintain the camera path across Efference devices. ## What you’ll do - Write and maintain sensor drivers, configure register maps and operating modes, and bring up camera modules on prototype and production boards. - Integrate MIPI CSI-2 capture and Linux camera interfaces, including V4L2 subdevices, media graphs, and sensor-to-ISP control paths. - Implement exposure, gain, frame-rate, trigger, and synchronization controls, with accurate metadata describing when and how each frame was captured. - Validate multi-camera timing and camera/IMU alignment with instrumented measurements, including readout timing and timestamp behavior under load. - Optimize frame delivery through buffers and DMA paths; diagnose corrupted images, frame drops, stalls, bandwidth limits, and recovery after disconnects. - Build sensor diagnostics and automated capture tests, working with ISP and factory teams on calibration, acceptance testing, and production issues. ## What we are looking for - Experience developing embedded camera software, sensor drivers, or low-level imaging pipelines. - Strong C/C++ skills and practical knowledge of Linux drivers, device trees, and hardware/software debugging. - Understanding of sensor timing, MIPI CSI-2, I2C/SPI control, and RAW/Bayer and YUV pixel formats. - Ability to read sensor datasheets, register maps, and schematics and verify behavior with lab instruments. - Experience isolating problems across the sensor, capture hardware, driver, and downstream image-processing path. ## Nice to Have - Experience with global-shutter sensors, stereo cameras, external triggering, or camera/IMU synchronization. - Work with NVIDIA, Qualcomm, Ambarella, Rockchip, or similar camera SoCs and their vendor tooling. - Knowledge of ISP control loops, DMA-BUF, GStreamer, or factory camera calibration. --- # Video Compression Engineer Canonical page: https://efference.ai/careers/video-compression-engineer/ Video Compression Engineer at Efference. San Francisco · Full time · On-site. You'll reduce the bandwidth needed to send robot video to shared compute while preserving the information robot models depend on. You'll reduce the bandwidth needed to send robot video to shared compute while preserving the information robot models depend on. You'll own the path from ISP output through encoding and work with wireless and evaluation engineers to adapt compression to network conditions and task requirements. ## What you’ll do - Build low-latency encoding pipelines on embedded hardware, tuning bitrate, quantization, frame structure, resolution, and frame rate for robot workloads. - Develop adaptive compression policies using link capacity, queue age, scene motion, and task feedback, with stable behavior as network conditions change. - Work with ISP engineers on noise, sharpening, exposure, and temporal processing to improve compressibility without removing task-relevant detail. - Measure rate-distortion curves alongside VIO, perception, and robot-policy outcomes; identify where additional compression causes a meaningful loss of capability. - Optimize buffer management, memory transfers, hardware encoder use, and decoder handoff so compression saves bandwidth without adding avoidable delay. - Test packet loss, reference-frame recovery, abrupt scene changes, and encoder reconfiguration; maintain reproducible benchmarks across cameras, codecs, and hardware versions. ## What we are looking for - Experience implementing or tuning video codecs, embedded media systems, or real-time image-processing pipelines. - Strong understanding of H.264/H.265, prediction structures, rate control, quantization, and the tradeoffs between quality, bitrate, and latency. - Proficiency in C/C++ on Linux and experience with frameworks such as V4L2, GStreamer, or FFmpeg. - Ability to profile memory movement, CPU load, and hardware codec behavior and resolve frame drops or unexpected buffering. - Experience designing controlled video experiments and interpreting both image-quality metrics and downstream application results. ## Nice to Have - Experience with learned compression, region-of-interest coding, or compression optimized for machine vision. - Knowledge of ISP tuning, RAW/Bayer data, hardware codecs, or zero-copy camera pipelines. - Work on real-time transport, congestion feedback, or robotic-policy evaluation under visual degradation. --- # Image Processing Engineer, Video Stabilization & Motion Estimation Canonical page: https://efference.ai/careers/camera-algorithm-engineer-stabilization/ Image Processing Engineer, Video Stabilization & Motion Estimation at Efference. San Francisco · Full time · On-site. You'll develop motion estimation and video stabilization for cameras carried by robots that walk, turn, vibrate, and interact with their surroundings. You'll develop motion estimation and video stabilization for cameras carried by robots that walk, turn, vibrate, and interact with their surroundings. You'll make video useful for perception and teleoperation while accounting for the geometry, timing, and field of view that downstream systems require. ## What you’ll do - Develop image-based, gyro-based, and hybrid motion estimation and stabilization algorithms for wide-angle, fisheye, and conventional camera systems. - Build camera/IMU calibration and alignment methods with the VIO and embedded teams, identifying bias, timing offsets, and mechanical changes that affect compensation. - Implement warping and reprojection that handle rolling-shutter distortion, rapid rotations, vibration, and motion blur within the device's compute budget. - Evaluate the tradeoffs between residual motion, crop, geometric distortion, temporal filtering, and added latency on representative robot trajectories. - Preserve the calibration and transform metadata needed by downstream consumers; test when VIO or policy inference should use original rather than stabilized frames. - Prototype in Python and ship optimized implementations on embedded processors, with regression tests for motion accuracy, visual artifacts, compression, and task performance. ## What we are looking for - Hands-on experience developing video stabilization, optical flow, camera motion estimation, or closely related geometric vision algorithms. - Strong understanding of camera models, projective geometry, image warping, and the limits of motion estimates in difficult scenes. - Experience with IMUs, sensor fusion, and spatial and temporal calibration between camera and inertial measurements. - Strong C++ and Python skills and experience turning algorithm prototypes into real-time implementations. - Ability to evaluate long video sequences and explain failure cases using measurements, image evidence, and a clear understanding of the camera pipeline. ## Nice to Have - Experience with robotics, action cameras, drones, or AR/VR tracking systems. - Work with learned optical flow, neural motion estimation, or hardware-accelerated image warping. - Knowledge of VIO/SLAM, ISP tuning, global-shutter sensors, or embedded GPU/DSP/NPU deployment. --- # Image Processing Engineer, HDR & Tone Mapping Canonical page: https://efference.ai/careers/research-engineer-hdr-video/ Image Processing Engineer, HDR & Tone Mapping at Efference. San Francisco · Full time · On-site. You'll develop HDR video processing that preserves useful scene information as robots move through changing light. You'll develop HDR video processing that preserves useful scene information as robots move through changing light. You'll work on exposure fusion and tone mapping with particular attention to temporal stability, motion artifacts, and the effect of image processing on compression and robot perception. ## What you’ll do - Develop global, local, and adaptive tone-mapping algorithms for continuous video, balancing shadow detail, highlight retention, contrast, and temporal consistency. - Work with sensor and ISP engineers on HDR capture and exposure fusion, accounting for readout timing, motion, saturation, and noise. - Diagnose and reduce flicker, brightness pumping, halos, ghosting, and unstable local contrast during movement and abrupt lighting transitions. - Build test sequences covering backlighting, reflective surfaces, low light, LED flicker, and transitions between indoor and outdoor illumination. - Measure how tone curves and fusion choices affect codec bitrate, feature tracking, depth, and policy performance with compression and robotics engineers. - Prototype algorithms in Python and deploy efficient embedded implementations, maintaining temporal regression tests and traceable parameter changes. ## What we are looking for - Experience developing HDR imaging, tone mapping, exposure fusion, or related camera algorithms for video. - Strong understanding of image formation, sensor dynamic range, exposure control, color processing, and noise. - Practical knowledge of temporal filtering and motion handling, including why a method that works on one image can fail on a sequence. - Strong C++ and Python skills and experience profiling algorithms against memory and compute limits. - Ability to design repeatable image-quality experiments and connect observed artifacts to their causes in the processing pipeline. ## Nice to Have - Experience with multi-exposure or sensor-level HDR, RAW/Bayer processing, and ISP hardware blocks. - Work on learned tone mapping, temporal neural models, or quantized deployment on embedded accelerators. - Knowledge of HDR transfer functions and formats, video compression, or the sensitivity of vision models to photometric changes. --- # Image Quality Engineer, ISP Tuning Canonical page: https://efference.ai/careers/camera-image-quality-tuning-engineer/ Image Quality Engineer, ISP Tuning at Efference. San Francisco · Full time · On-site. You'll tune Efference camera pipelines to produce consistent, useful images across the conditions robots encounter. You'll tune Efference camera pipelines to produce consistent, useful images across the conditions robots encounter. You'll evaluate image quality in the lab and field, balancing detail, noise, exposure, and temporal behavior with the needs of compression and downstream perception. ## What you’ll do - Tune exposure and white balance, lens shading, color correction, denoising, sharpening, gamma, and tone curves across sensor modes and lighting conditions. - Build and maintain representative scenes and capture sets, including motion, low light, mixed illumination, backlighting, and difficult materials. - Compare tuning revisions using objective measurements and careful image review; identify texture loss, clipping, color shifts, temporal artifacts, and inconsistent cameras. - Work with compression, VIO, depth, and evaluation engineers to test how tuning changes affect bitrate and robot performance. - Use Python tools to analyze RAW and processed captures, run parameter sweeps, and make comparisons reproducible across firmware and calibration versions. - Investigate unit and supplier variation, support factory calibration, and maintain versioned tuning packages with clear release criteria. ## What we are looking for - Hands-on experience with camera tuning, image-quality evaluation, or imaging projects that required systematic capture and analysis. - Understanding of exposure, white balance, noise, sharpness, color, dynamic range, and the main blocks of an ISP. - Ability to identify image and video artifacts precisely and design a test that separates their possible causes. - Python or C/C++ skills and comfort working with image datasets, analysis scripts, and version control. - Careful lab and field practice, with an ability to explain tuning decisions and tradeoffs to camera and perception engineers. ## Nice to Have - Experience with vendor ISP tuning tools, RAW/Bayer processing, or multi-camera color and exposure matching. - Familiarity with MTF/SFR, texture, SNR, color accuracy, dynamic-range measurement, or temporal image-quality metrics. - Experience with production camera calibration, robotics, machine vision, photography, or video capture. --- # Image Processing Engineer, Testing & Automation Canonical page: https://efference.ai/careers/camera-iq-test-software-engineer/ Image Processing Engineer, Testing & Automation at Efference. San Francisco · Full time · On-site. You'll build the tools and test systems that let our imaging team measure changes quickly and trust the results. You'll build the tools and test systems that let our imaging team measure changes quickly and trust the results. You'll combine camera testing with software development, turning image-quality experiments and field failures into repeatable checks across devices and software versions. ## What you’ll do - Build automated capture and analysis tools for RAW images, processed frames, video, and the metadata needed to reproduce each result. - Develop controlled test setups for lighting, charts, motion, and camera configuration, working with algorithm engineers to define measurable acceptance criteria. - Implement metrics for spatial detail, noise, exposure, color, dynamic range, and temporal artifacts; validate the metrics against known defects. - Maintain versioned datasets and comparison reports that connect each capture to hardware revision, calibration, ISP settings, and firmware build. - Integrate camera and image-processing tests into continuous integration, with useful failure artifacts and reliable handling of lab equipment and device resets. - Reproduce imaging bugs, reduce them to test cases, and maintain regression coverage as algorithms and sensors change. ## What we are looking for - Strong Python skills and experience building maintainable test, data-processing, or automation software. - Hands-on experience with cameras, image processing, or computer vision through industry, research, or substantial technical projects. - Understanding of basic image-quality concepts and an ability to distinguish an algorithm defect from capture or measurement variation. - Comfort with Linux, Git, automated tests, and organizing datasets so another engineer can reproduce an analysis. - Attention to experimental detail and an ability to communicate failures with clear evidence and practical next steps. ## Nice to Have - Experience with OpenCV, NumPy, C++, image-quality measurement tools, or camera-control interfaces. - Work on programmable lighting, motion stages, robotic test rigs, or hardware-in-the-loop automation. - Experience with embedded camera platforms, containerized test runners, or large video regression datasets. --- # Optical Systems Engineer, Cameras Canonical page: https://efference.ai/careers/camera-optical-engineer/ Optical Systems Engineer, Cameras at Efference. San Francisco · Full time · On-site. You'll develop the optics for Efference cameras, from optical requirements and lens selection through qualification and production. You'll develop the optics for Efference cameras, from optical requirements and lens selection through qualification and production. You'll work with sensor, ISP, and compression engineers to preserve the scene information robots need at the resolution and bandwidth the system can support. ## What you’ll do - Translate robot tasks and camera constraints into requirements for field of view, focal length, aperture, working distance, distortion, and image-plane performance. - Evaluate existing lenses and develop custom designs with suppliers, accounting for sensor format, chief-ray angle, cover glass, filters, size, and cost. - Model and measure MTF, relative illumination, chromatic aberration, distortion, stray light, flare, and focus across the field and operating temperature. - Perform tolerance and sensitivity analysis, then define alignment and assembly procedures that maintain optical performance across production variation. - Compare optical choices in the full camera pipeline, measuring the detail retained after sampling, ISP processing, and compression alongside downstream task results. - Qualify suppliers and modules, establish inspection limits, and investigate yield or field issues using correlated optical, mechanical, and image data. ## What we are looking for - Experience designing, integrating, or characterizing imaging optics and camera modules. - Strong grounding in geometrical and physical optics and an understanding of how lens performance interacts with CMOS sensors. - Working knowledge of Zemax OpticStudio, CODE V, or equivalent optical design and analysis tools. - Hands-on experience with optical metrology, lens tolerancing, alignment, and meaningful comparison of simulation and measurement. - Ability to work directly with suppliers and explain optical tradeoffs to electrical, imaging, and manufacturing engineers. ## Nice to Have - Experience taking compact, wide-angle, stereo, or machine-vision cameras into production. - Knowledge of active alignment, optical coatings, filters, environmental stability, or camera calibration. - Python or MATLAB skills and experience with design of experiments, measurement repeatability, or production yield analysis. --- # Computer Vision Engineer, VIO / SLAM Canonical page: https://efference.ai/careers/research-engineer-vio-slam/ Computer Vision Engineer, VIO / SLAM at Efference. San Francisco · Full time · On-site. You'll develop Efference's visual-inertial odometry and mapping stack, including the calibration that makes its outputs trustworthy. You'll develop Efference's visual-inertial odometry and mapping stack, including the calibration that makes its outputs trustworthy. You'll combine geometric estimation with learned components where they help, deploying the system on our embedded compute and measuring how imaging and compression choices affect localization. ## What you’ll do - Build visual-inertial estimation covering feature tracking, initialization, pose estimation, sensor fusion, relocalization, and mapping for real robot motion. - Develop camera and IMU intrinsic, extrinsic, and temporal calibration, with procedures that can be used during development and manufacturing. - Investigate classical, learned, and hybrid front ends; optimize suitable learned components for our NPU while maintaining the estimation pipeline's accuracy and timing. - Quantify sensitivity to exposure, blur, rolling shutter, ISP processing, frame loss, compression, and synchronization error with the camera and wireless teams. - Build benchmarks for trajectory error, drift, tracking loss, recovery, and runtime using recorded sequences and physical ground truth. - Ship maintainable C++ implementations with calibrated coordinate frames, timestamps, uncertainty estimates, and diagnostics for downstream robotics software. ## What we are looking for - Substantial experience developing VIO, SLAM, visual odometry, or multi-sensor state estimation. - Strong understanding of multi-view geometry, camera models, nonlinear optimization, and probabilistic estimation. - Experience with IMU measurements and camera/IMU calibration, including the effect of timing and noise models on observability. - Strong C++ and Python skills and a record of evaluating algorithms on real sensor data. - Ability to diagnose tracking failures and improve both the algorithm and the surrounding sensor pipeline. ## Nice to Have - Experience with learned feature extraction, optical flow, depth, neural odometry, or embedded NPU deployment. - Work with fisheye or global-shutter cameras and libraries such as Ceres, GTSAM, Eigen, or OpenCV. - Experience with factory calibration, motion-capture ground truth, or VIO on legged and mobile robots. --- # Computer Vision Engineer, Neural ISP & Depth Canonical page: https://efference.ai/careers/research-engineer-neural-isp/ Computer Vision Engineer, Neural ISP & Depth at Efference. San Francisco · Full time · On-site. You'll develop neural image-processing and depth models that run on Efference devices and improve robot perception. You'll develop neural image-processing and depth models that run on Efference devices and improve robot perception. You'll own the work from training data and model design through NPU deployment, checking that gains in image quality or depth accuracy hold up in real robotic tasks. ## What you’ll do - Develop neural and hybrid ISP pipelines for RAW processing, denoising, demosaicing, HDR, and other imaging problems where learning improves the system. - Build monocular, stereo, or multi-camera depth models with explicit evaluation of scale, boundary quality, temporal consistency, and uncertainty. - Construct training and validation datasets, loss functions, and ablations that expose behavior under motion, low light, reflective surfaces, and unfamiliar scenes. - Optimize architectures, quantization, operator support, memory use, and data movement for our NPU; profile performance on the actual device. - Measure geometric fidelity and failure modes, including invented detail or unstable depth, with image-quality, VIO, and robotics evaluation engineers. - Integrate models into versioned camera pipelines and maintain repeatable comparisons of task performance, runtime, power, and bandwidth. ## What we are looking for - Experience developing deep-learning models for image restoration, computational imaging, stereo, depth estimation, or related geometric vision tasks. - Strong Python and PyTorch skills, with experience building training pipelines and running controlled experiments. - Understanding of image formation, camera geometry, and the classical processing methods relevant to your models. - Experience optimizing or deploying models under real compute, memory, or latency constraints. - Ability to analyze failure cases and distinguish a better benchmark score from an improvement that matters in a deployed perception system. ## Nice to Have - Direct experience with RAW/Bayer data, ISP tuning, multi-view calibration, or temporal video models. - Work on NPU toolchains, quantization-aware training, custom operators, or hardware-aware architecture design. - Research or production work in robot perception, learned compression, or joint optimization of imaging and downstream tasks. --- # Electrical Engineer, PCB Design Canonical page: https://efference.ai/careers/electrical-engineer-pcb/ Electrical Engineer, PCB Design at Efference. San Francisco · Full time · On-site. You'll design the electronics for Efference's Mono, Stereo, and Node products and take the boards from architecture through production. You'll design the electronics for Efference's Mono, Stereo, and Node products and take the boards from architecture through production. You'll work closely with camera, RF, embedded, and manufacturing engineers to build hardware that meets the system's timing, bandwidth, power, and reliability requirements. ## What you’ll do - Own schematics, component selection, PCB constraints, and layout reviews for compute, camera, wireless, power, and sensor interfaces. - Design power sequencing, clock distribution, protection, and high-speed interconnects, with clear budgets for signal integrity and power integrity. - Bring up boards in the lab, write validation plans, and debug issues across hardware, firmware, and connected peripherals. - Work with RF engineers and the product design team on antenna integration, grounding, shielding, connector placement, and thermal constraints. - Release fabrication and assembly packages, manage engineering changes, and support contract manufacturers through prototype builds and production ramp. - Design for assembly, test, and repair; investigate manufacturing failures and qualify component substitutions with the technical buyer and subsystem owners. ## What we are looking for - Experience designing and bringing up multilayer PCBs for embedded, imaging, communications, or comparable electronic products. - Strong fundamentals in digital and analog circuits, power supplies, clocks, and high-speed signal behavior. - Proficiency in Altium, Cadence, or a comparable schematic and PCB design environment. - Hands-on skill with oscilloscopes, logic analyzers, power measurement, soldering, and systematic board debugging. - Experience working with manufacturers, maintaining a controlled BOM, and resolving issues between design release and a working build. ## Nice to Have - Experience with MIPI CSI-2, PCIe, DDR, Ethernet, USB, or RF interfaces on compact boards. - Work on stereo cameras, PoE, rigid-flex designs, or hardware synchronization between sensors. - Experience with EMC pre-compliance, signal-integrity simulation, automated board tests, or volume manufacturing. --- # Product Design Engineer Canonical page: https://efference.ai/careers/mechanical-engineer-robotics/ Product Design Engineer at Efference. San Francisco · Full time · On-site. You'll support our senior design lead on Mono, Stereo, and Node, bringing engineering analysis and hands-on testing to product development. You'll support our senior design lead on Mono, Stereo, and Node, bringing engineering analysis and hands-on testing to product development. Your work will focus on mechanical and thermal modeling, process engineering support, and integrating our hardware onto robots and data collection platforms. You'll also design mounts, accessories, and selected product details, then validate them through prototypes and tests. ## What you’ll do - Support the senior design lead with CAD, engineering calculations, tolerance analysis, and prototype evaluation for Mono, Stereo, and Node. - Build mechanical and thermal models to assess heat dissipation, stiffness, mounting loads, and vibration; check assumptions against physical measurements. - Plan and run bench and on-robot tests, instrument prototypes, analyze results, and use the findings to improve thermal performance, mechanical reliability, and mounting repeatability. - Integrate cameras and networking hardware onto robots, wearable systems, and data collection rigs, resolving sensor placement, fields of view, antenna clearance, cable routing, and service access. - Design and prototype mounts, accessories, fixtures, and selected enclosure details, refining them with the senior design lead and feedback from installation and use. - Help the manufacturing and process engineering team improve assembly, calibration, and test workflows through fixtures, work instructions, tolerance studies, and investigation of build variation. ## What we are looking for - Strong fundamentals in mechanics, heat transfer, geometry, and tolerances, with the ability to use calculations and models to guide practical design decisions. - Proficiency in 3D CAD and technical drawings, with experience developing mechanical parts, mounts, or fixtures that can be built and assembled. - Hands-on experience instrumenting and testing hardware, analyzing data, and comparing measured behavior with engineering predictions. - Experience integrating hardware under mechanical, electrical, and thermal constraints, including attention to installation, cable management, and maintenance. - Ability to work closely with a senior designer and manufacturing engineers, document assumptions and test results, and turn feedback into reliable product and process improvements. ## Nice to Have - Experience with UMI or similar robotics data collection platforms, including hardware setup, sensor mounting, and integration. - Experience designing or testing human wearables, with attention to attachment, fit, comfort, and motion during data collection. - Mechanical design or integration experience in robotics, including motors, actuators, end effectors, or camera and sensor mounts. - Experience with thermal simulation, finite element analysis, manufacturing fixtures, or repeatable assembly and calibration processes. --- # Manufacturing and Process Engineer Canonical page: https://efference.ai/careers/manufacturing-process-engineer/ Manufacturing and Process Engineer at Efference. San Francisco · Full time · On-site. You'll turn Efference hardware designs into repeatable production processes for Mono, Stereo, and Node. You'll turn Efference hardware designs into repeatable production processes for Mono, Stereo, and Node. You'll develop assembly and calibration workflows, choose where automation helps, and use production data to improve yield, throughput, and consistency. ## What you’ll do - Design the build process from incoming parts through assembly, calibration, inspection, and final test, with clear work instructions and traceability. - Develop fixtures, tooling, and automated stations for precise sensor placement, optical alignment, fastening, and other repeatability-sensitive operations. - Work with design engineers and suppliers on manufacturability, tolerance stacks, process capability, and changes that prevent recurring defects. - Introduce robotic handling or automation where it improves quality or capacity, validating the process against a simpler manual baseline. - Run pilot builds and production ramp with contract manufacturers, measuring cycle time, first-pass yield, rework, and station bottlenecks. - Use experiments and failure analysis to improve processes, and coordinate changes with test engineers so production limits and fixtures remain aligned. ## What we are looking for - Experience taking electronic or electromechanical products from prototype builds into repeatable manufacturing. - Hands-on experience with robotic automation or automated assembly, including fixturing, sensing, and station commissioning. - Understanding of design for assembly, tolerance analysis, process controls, and measurement repeatability. - Ability to develop fixtures and production documentation and analyze yield and cycle-time data using practical software tools. - Experience working directly with technicians, suppliers, and design engineers to solve problems on the production floor. ## Nice to Have - Experience manufacturing cameras, optical assemblies, RF devices, or compact embedded hardware. - Knowledge of active alignment, adhesives and curing, cleanliness controls, or precision calibration processes. - Experience with MES integration, statistical process control, design of experiments, or new factory line setup. --- # Robotics Researcher, Evaluations Canonical page: https://efference.ai/careers/senior-rse-model-inference-evaluation/ Robotics Researcher, Evaluations at Efference. San Francisco · Full time · On-site. You'll determine how changes in Efference's perception and compute infrastructure affect what robots can actually do. You'll determine how changes in Efference's perception and compute infrastructure affect what robots can actually do. You'll design experiments that connect camera quality, compression, timing, network behavior, and inference performance to reliable task completion on physical robots. ## What you’ll do - Build a suite of manipulation and mobile-robot tasks with clear success criteria, repeatable starting conditions, and representative failure cases. - Integrate and evaluate learned policies, including vision-language-action and imitation-learning models, across local and remote inference configurations. - Run controlled studies of bitrate, image processing, observation age, synchronization error, latency, and jitter, separating their effects from changes in the policy. - Measure task success, intervention rate, completion time, and recovery behavior with enough repeated trials to distinguish improvements from noise. - Maintain versioned datasets, checkpoints, environments, and run metadata; use held-out tasks or scenes to test whether results generalize. - Investigate failures with imaging, wireless, controls, and ML engineers, then turn the findings into product requirements and reproducible regression cases. ## What we are looking for - Hands-on experience deploying and evaluating learned policies on physical robots. - Strong Python skills and familiarity with a modern ML framework, robot middleware, and the practical debugging of perception-to-action systems. - Understanding of experimental design, statistical uncertainty, dataset leakage, and the limits of aggregate benchmark scores. - Ability to isolate failures across sensor input, model behavior, control, and hardware instead of attributing every failure to the model. - A record of turning research questions into experiments that others can reproduce and use to make engineering decisions. ## Nice to Have - Experience with VLA, diffusion, or flow-based policies and robot learning datasets or evaluation frameworks. - Work on robustness, distribution shift, sim-to-real transfer, or policy performance under sensor and network impairments. - Experience building automated robot test stations, ground-truth instrumentation, or large-scale evaluation pipelines. --- # Robotics Researcher, Teleoperation Canonical page: https://efference.ai/careers/senior-rse-teleoperation/ Robotics Researcher, Teleoperation at Efference. San Francisco · Full time · On-site. You'll develop teleoperation systems for collecting useful robot demonstrations and operating robots through Efference's perception and network stack. You'll develop teleoperation systems for collecting useful robot demonstrations and operating robots through Efference's perception and network stack. You'll study how video quality, viewpoint, delay, and control feedback affect operator performance, then use those results to improve the product. ## What you’ll do - Build teleoperation workflows using leader-follower devices, VR interfaces, or other input systems suited to the robot and task. - Develop retargeting, calibration, and command interfaces with controls engineers, accounting for kinematic differences and the limits of each platform. - Integrate synchronized video, robot state, and operator input, with instrumentation for the delay from observation to display and command to execution. - Run experiments on bitrate, frame rate, depth cues, camera placement, jitter, and dropped observations to measure task quality and operator workload. - Record demonstrations with aligned actions and observations, preserving session metadata, interventions, and quality flags for training and evaluation. - Implement and test pause, handoff, reconnect, and local fallback behavior with the controls team; use operator feedback to improve difficult workflows. ## What we are looking for - Experience building teleoperation, robot learning data collection, or interactive robotics systems on physical hardware. - Strong Python or C++ skills and an understanding of robot kinematics, coordinate frames, calibration, and control interfaces. - Practical knowledge of real-time video, network delay, and the synchronization of heterogeneous sensor and action streams. - Ability to design experiments with operators and distinguish an interface problem from a control, perception, or network problem. - Experience producing documented, usable demonstration data and maintaining the equipment and software needed to collect it. ## Nice to Have - Experience with OpenXR, Unity, stereo rendering, hand tracking, haptics, or wearable data collection. - Work on bimanual manipulation, humanoid retargeting, shared autonomy, or learning from demonstrations. - Experience with remote operation over variable networks and evaluating operator comfort and performance over long sessions. --- # Robotics Software Engineer, Controls Canonical page: https://efference.ai/careers/senior-rse-controls/ Robotics Software Engineer, Controls at Efference. San Francisco · Full time · On-site. You'll connect remotely served robot policies and teleoperation inputs to reliable motion on physical robots. You'll connect remotely served robot policies and teleoperation inputs to reliable motion on physical robots. You'll develop the local control and execution software needed to evaluate Efference infrastructure, making timing, stale observations, and interrupted connectivity explicit parts of the system design. ## What you’ll do - Implement robot interfaces and local execution loops for joint, Cartesian, and trajectory commands, working within each platform's supported control modes. - Integrate learned policies with state estimation, command interpolation, action buffering, and feedback so inference outputs can be executed consistently. - Define and test behavior for late, missing, duplicated, or out-of-order commands, including command expiry, local watchdogs, and controlled stopping. - Characterize how network delay, observation age, sensor noise, and action cadence affect tracking error and task performance. - Develop simulation and hardware tests for controller behavior, then validate the assumptions on physical robots with measured dynamics and real sensors. - Work with evaluation and teleoperation researchers to expose useful diagnostics and improve control interfaces across supported embodiments. ## What we are looking for - Experience developing and deploying robot control software on physical hardware. - Strong understanding of rigid-body kinematics, dynamics, feedback control, trajectory generation, and coordinate transformations. - Proficiency in C++ and Python and experience with timing-sensitive software, concurrency, and hardware interfaces. - Ability to diagnose instability or poor tracking using logs, measurements, and a clear model of the system. - Practical judgment about operating limits and local fault handling when upstream software or communications fail. ## Nice to Have - Experience with manipulation, impedance control, inverse dynamics, model predictive control, or whole-body control. - Work with MuJoCo, Pinocchio, Drake, ROS 2, or real-time Linux. - Experience deploying learned controllers, executing action chunks, or testing networked control systems. --- # Robotics Software Engineer, Infrastructure Canonical page: https://efference.ai/careers/rse-infrastructure/ Robotics Software Engineer, Infrastructure at Efference. San Francisco · Full time · On-site. You'll build the robot-side software and development infrastructure used to integrate, test, and operate Efference across different robot platforms. You'll build the robot-side software and development infrastructure used to integrate, test, and operate Efference across different robot platforms. You'll make sensor capture, model execution, recording, and deployment reproducible so researchers and customers can diagnose problems without rebuilding the same tools. ## What you’ll do - Develop reusable robot adapters and runtime services for sensor streams, state, calibration, and inference interfaces, with clear timestamp and coordinate-frame contracts. - Build synchronized recording, data validation, upload, and replay workflows that preserve provenance across cameras, actions, policies, and software versions. - Maintain reproducible builds, development environments, configuration management, and automated integration tests across supported robot computers. - Implement deployment and fleet-health services, including staged updates, rollback, remote diagnostics, and version compatibility checks. - Profile inter-process communication, serialization, buffering, and memory use so infrastructure does not consume the latency budget needed by perception and control. - Work with SDK, full-stack, and ML infrastructure engineers to connect robot services to customer tools, evaluation systems, and cloud compute. ## What we are looking for - Experience building software infrastructure for robots, autonomous systems, or hardware fleets. - Strong C++ and Python skills, Linux fluency, and an understanding of concurrent systems and software interfaces. - Experience with sensor data, timestamps, calibration, and the operational problems that arise when multiple software components share a robot. - A record of building reliable deployment, testing, observability, or data tools used by other engineers. - Ability to debug across a large codebase and make a failure reproducible before deciding where the fix belongs. ## Nice to Have - Experience with ROS 2, DDS, shared-memory IPC, MCAP, or comparable robot data and middleware tools. - Work on fleet updates, hardware-in-the-loop CI, cross-compilation, or embedded performance profiling. - Experience with robot learning workflows, dataset versioning, remote inference, or production device security. --- # Machine Learning Infrastructure Engineer, Orchestration Canonical page: https://efference.ai/careers/ml-infrastructure-engineer-cluster-orchestration/ Machine Learning Infrastructure Engineer, Orchestration at Efference. San Francisco · Full time · On-site. You'll build the compute platform that schedules and runs robot models on shared GPUs. You'll build the compute platform that schedules and runs robot models on shared GPUs. You'll own placement, model lifecycle, and service reliability across inference, training, and evaluation workloads, accounting for the latency and continuity requirements of active robot sessions. ## What you’ll do - Develop scheduling and admission control based on model memory, accelerator capacity, session requirements, and measured network and inference latency. - Build model loading, warm pools, caching, and container lifecycle management to reduce startup delays and avoid disruption during capacity changes. - Coordinate inference-serving behavior with performance engineers, balancing batching and GPU utilization against observation freshness and response deadlines. - Isolate customer workloads and manage quotas, resource contention, and priority so background training or evaluation cannot silently degrade live robot sessions. - Implement health checks, failure recovery, staged model rollouts, and rollback, preserving the session and version information needed to diagnose incidents. - Instrument queue time, GPU utilization, memory pressure, deadline misses, and serving cost; use workload replay and load tests to guide capacity planning. ## What we are looking for - Experience building distributed infrastructure, schedulers, runtimes, or ML platforms that run production workloads. - Strong systems programming in Go, Rust, C++, or Python and sound judgment about concurrency, failures, and consistency. - Understanding of Linux, containers, networking, storage, and how resource limits affect application performance. - Experience operating services with clear reliability targets and debugging problems across application and infrastructure boundaries. - Ability to translate workload measurements into scheduling and architecture decisions, including tradeoffs between utilization and latency. ## Nice to Have - Experience with Kubernetes, Ray, Slurm, custom schedulers, or GPU-aware container runtimes. - Work on inference serving, checkpoint/restore, model caching, multi-GPU workloads, or accelerator isolation. - Experience with latency-sensitive robotics, multimodal models, or scheduling mixed training and inference workloads. --- # Machine Learning Infrastructure Engineer, Kernel Optimization Canonical page: https://efference.ai/careers/ml-infrastructure-engineer-gpu-systems/ Machine Learning Infrastructure Engineer, Kernel Optimization at Efference. San Francisco · Full time · On-site. You'll make robot models run efficiently on datacenter GPUs, reducing inference latency and the compute cost of serving a fleet. You'll make robot models run efficiently on datacenter GPUs, reducing inference latency and the compute cost of serving a fleet. You'll work from model-level profiling down to GPU kernels, verifying that each optimization preserves the behavior the robot depends on. ## What you’ll do - Profile representative perception and robot-policy workloads, separating kernel execution, memory movement, synchronization, launch overhead, and CPU bottlenecks. - Implement and optimize CUDA or Triton kernels for expensive operators, using fusion, tiling, suitable layouts, and reduced memory traffic where they help. - Improve inference graphs and execution paths through compilation, graph capture, allocation reuse, and elimination of unnecessary host-device transfers. - Evaluate precision and quantization choices with researchers, checking numerical error and closed-loop task performance alongside speed and memory use. - Benchmark realistic batch sizes, sequence lengths, image shapes, and concurrent sessions with the orchestration team, including tail latency under contention. - Maintain correctness and performance regression tests across hardware and software versions, and upstream improvements where a shared library is the right home. ## What we are looking for - Experience delivering measured performance improvements in GPU workloads or high-performance ML systems. - Strong CUDA or comparable GPU programming skills and understanding of memory hierarchies, occupancy, synchronization, and parallel execution. - Proficiency in C++ and Python and experience with PyTorch or another major ML framework. - Ability to use profiling tools to identify the limiting resource and choose an optimization that addresses it. - Careful benchmarking and correctness practice, including handling precision changes and separating microbenchmark gains from application gains. ## Nice to Have - Experience with Triton, CUTLASS, TensorRT, compiler internals, or custom framework operators. - Work on attention, vision encoders, diffusion or flow models, and small-batch latency-sensitive inference. - Experience with multi-GPU communication, training kernels, model parallelism, or performance tuning for shared accelerators. --- # Software Engineer, Full-Stack Canonical page: https://efference.ai/careers/software-engineer-full-stack/ Software Engineer, Full-Stack at Efference. San Francisco · Full time · On-site. You'll build the software people use to configure, manufacture, deploy, and monitor Efference products. You'll build the software people use to configure, manufacture, deploy, and monitor Efference products. Your scope will include customer interfaces, internal factory tools, backend services, and the website, with priorities shaped by where working software can remove the most friction. ## What you’ll do - Build web applications and backend APIs for device provisioning, configuration, fleet status, diagnostics, and deployment workflows. - Develop factory tools for serial numbers, calibration records, test results, assembly history, and inventory handoffs with manufacturing and operations teams. - Design data models and integrations that keep hardware identity, software versions, customer accounts, and operational history consistent. - Turn streaming telemetry and test data into useful interfaces, with clear handling of stale information, partial failures, and actions that affect physical devices. - Implement authentication, permissions, audit trails, and reliable deployment practices for the services you own. - Work with design and growth on the website and product presentation, and observe customers and factory users to improve workflows after release. ## What we are looking for - Experience shipping web applications across frontend, backend, and database layers. - Strong TypeScript/JavaScript skills and proficiency in a backend language such as Python, Go, or Rust. - Understanding of API design, relational data modeling, asynchronous jobs, and the failure modes of production services. - Ability to turn an operational problem into a simple interface and maintain it through changing requirements. - Experience with automated testing, observability, and practical security, plus comfort working directly with technical and nontechnical users. ## Nice to Have - Experience with React, PostgreSQL, real-time dashboards, or hardware fleet management. - Work on manufacturing, warehouse, quality, or calibration software that must preserve traceability. - Experience with device provisioning, OTA workflows, developer tools, or careful implementation of a visual design system. --- # Software Engineer, SDKs Canonical page: https://efference.ai/careers/software-engineer-sdks/ Software Engineer, SDKs at Efference. San Francisco · Full time · On-site. You'll own the SDKs that let robotics developers use Efference hardware and cloud services. You'll own the SDKs that let robotics developers use Efference hardware and cloud services. You'll make capture, synchronization, streaming, and inference straightforward to integrate, with clear behavior when devices, networks, or software versions change. ## What you’ll do - Design and implement Python and C++ APIs for device discovery, configuration, synchronized capture, stream access, and remote inference. - Define consistent contracts for timestamps, calibration, coordinate frames, memory ownership, errors, and connection lifecycle across the SDK. - Build integrations and working examples for robot middleware, embedded platforms, and ML workflows, keeping examples tested against supported releases. - Implement async and streaming interfaces with bounded buffering, cancellation, timeouts, and useful diagnostics under load or network interruption. - Own packaging, compatibility testing, documentation, versioning, and migration paths across host operating systems, architectures, firmware, and cloud APIs. - Work with solutions engineers and customers to reproduce integration problems and turn recurring workarounds into stable product features. ## What we are looking for - Experience building SDKs, libraries, developer tools, or APIs used by engineers outside your immediate team. - Strong Python and C++ skills and an understanding of concurrency, resource lifetime, and language boundaries. - Ability to design interfaces that are easy to use correctly and expose enough information to debug difficult failures. - Experience with automated compatibility tests, packaging, releases, and documentation that stays aligned with code. - Comfort working directly with users and balancing API stability against the need to improve the product. ## Nice to Have - Experience with ROS 2, Jetson, camera or sensor SDKs, and robotics model integrations. - Work with native bindings, zero-copy arrays, streaming RPCs, or low-latency media interfaces. - Experience maintaining open-source libraries, cross-platform build systems, or hardware-backed CI. --- # Product, Design Canonical page: https://efference.ai/careers/product-designer-software/ Product, Design at Efference. San Francisco · Full time · On-site. You'll shape how Efference looks and how people understand what we build. You'll shape how Efference looks and how people understand what we build. You'll own the company's visual identity and design direction across the website, product communication, and marketing, working closely with engineering to make a technical product clear and recognizable. ## What you’ll do - Develop a visual identity and design system that carries consistently across the website, documentation, presentations, product launches, and events. - Turn sensor, networking, and compute concepts into clear diagrams, demonstrations, and product stories grounded in how the system actually works. - Design the website and key customer-facing workflows with full-stack engineers, carrying work from early concepts through implementation and review. - Create launch materials, photography direction, motion studies, and other assets that show the hardware and its use on real robots. - Work with industrial design on a coherent relationship between physical products, packaging, interfaces, and the company identity. - Observe how customers understand the product, revise confusing material, and maintain reusable assets and guidance as the team grows. ## What we are looking for - A portfolio showing strong typography, composition, visual systems, and finished work across digital or physical touchpoints. - Experience translating a technical product into communication that is accurate and easy to understand. - Ability to move from concept to detailed execution and work closely with engineers on the final implementation. - Proficiency in modern design and prototyping tools, with sound judgment about hierarchy, interaction, and visual consistency. - A clear point of view, an ability to explain your decisions, and a willingness to revise work in response to evidence and useful criticism. ## Nice to Have - Experience with hardware, robotics, developer products, infrastructure, or technical brands. - Skills in motion, 3D, photography, illustration, or frontend development. - Experience building a company identity early, directing external creative partners, or designing product launches. --- # Growth & Partnerships Lead Canonical page: https://efference.ai/careers/growth-marketing-lead/ Growth & Partnerships Lead at Efference. San Francisco · Full time · On-site. You'll find the robotics teams whose deployments benefit most from Efference and turn that demand into lasting customer relationships. You'll find the robotics teams whose deployments benefit most from Efference and turn that demand into lasting customer relationships. You'll own customer-facing sales and marketing, working with solutions engineers to move opportunities from an initial conversation through evaluation and adoption. ## What you’ll do - Identify prospective customers among robotics companies and model developers, and learn where perception, connectivity, or compute constrains their products. - Build a qualified pipeline through direct outreach, introductions, technical content, and relevant industry and research communities. - Structure evaluations with a defined use case, technical owner, success criteria, timeline, and commercial next step in partnership with Solutions Engineering. - Work with founders on positioning, packaging, pricing, and commercial proposals, using customer evidence and deployment economics to guide decisions. - Track evaluation conversion, deployment progress, retention, and expansion; bring buying objections and repeated product requests into planning. ## What we are looking for - Experience growing a technical product through customer-facing sales and marketing. - Ability to understand a customer's technical constraints and connect product capabilities to a practical business case. - A record of developing relationships and following opportunities through evaluation, negotiation, and adoption. - Strong written and verbal communication, including clear outreach, proposals, and discussions with engineering leaders. - Commercial judgment, organized follow-through, and willingness to do the research and operational work needed to win and retain customers. ## Nice to Have - Experience with robotics, semiconductors, cloud compute, industrial systems, or developer infrastructure. - Existing relationships with robotics teams, model developers, research labs, or companies deploying robots. - Experience with design partnerships, technical launches, usage-based products, or hardware-plus-software business models. --- # Chief of Staff Canonical page: https://efference.ai/careers/chief-of-staff/ Chief of Staff at Efference. San Francisco · Full time · On-site. You'll work directly with Efference's founders to turn company priorities into completed work across engineering, customers, hiring, and operations. You'll work directly with Efference's founders to turn company priorities into completed work across engineering, customers, hiring, and operations. You'll own projects that cross team boundaries, make decisions and dependencies visible, and build practical operating habits as the company grows. ## What you’ll do - Maintain a clear view of company priorities, milestones, owners, and dependencies across product development, manufacturing, and customer deployments. - Prepare planning and operating reviews, identify stalled decisions, and follow actions through to a result with the responsible teams. - Take on defined projects that lack an owner, such as a new operating process, a company-wide rollout, or preparation for a major customer milestone. - Build concise analyses of headcount, spending, capacity, and business performance with the relevant owners, making assumptions and tradeoffs explicit. - Help prepare investor and board materials, maintain supporting information, and coordinate diligence and external advisers when needed. - Improve hiring coordination, onboarding, internal communication, and information access without adding process that slows the team down. ## What we are looking for - Experience taking ambiguous business or operational projects from a loosely defined problem to an implemented result. - Strong analytical ability and comfort working with spreadsheets, operating metrics, budgets, and incomplete information. - Clear writing and an ability to summarize a complex issue, identify the decision needed, and recommend a practical next step. - Judgment and discretion when handling sensitive company information, competing priorities, and difficult conversations. - Ability to earn trust across technical and nontechnical teams, follow through on details, and challenge a plan constructively. ## Nice to Have - Experience at an early hardware, robotics, infrastructure, or other technically complex company. - Work in business operations, technical program management, finance, consulting, or company building with direct execution responsibility. - Experience supporting fundraising, recruiting, manufacturing ramp, or enterprise customer deployments. --- # Technical Buyer, Electronics & Hardware Canonical page: https://efference.ai/careers/technical-buyer-electronics-hardware/ Technical Buyer, Electronics & Hardware at Efference. San Francisco · Full time · On-site. You'll source the components and manufacturing services needed to build Efference products, from engineering prototypes through production. You'll source the components and manufacturing services needed to build Efference products, from engineering prototypes through production. You'll work closely with design and manufacturing engineers to keep material available, control cost, and resolve supply problems before they hold up a build. ## What you’ll do - Source sensors, processors, memory, radios, optical modules, PCB assemblies, and mechanical parts from qualified suppliers and manufacturing partners. - Run requests for quotation, compare technical and commercial proposals, and negotiate price, lead time, minimum order quantities, tooling, and payment terms. - Maintain purchase orders and supplier commitments against the BOM, engineering changes, inventory position, and build schedule. - Track shortages, lifecycle changes, and single-source risks; work with engineering to qualify alternatives before purchasing substitutions. - Evaluate supplier cost, capacity, quality, and delivery performance with manufacturing, and resolve discrepancies or missed commitments directly. - Coordinate material readiness and receiving handoffs with supply chain operations, maintaining accurate part, supplier, revision, and cost records. ## What we are looking for - Experience buying electronic components, PCB assemblies, or technical hardware for development and production. - Ability to read BOMs, drawings, and component specifications well enough to ask useful questions and identify sourcing risks. - Experience with supplier qualification, quotation analysis, negotiation, and purchase-order management. - Strong spreadsheet and planning skills, with careful handling of revisions, lead times, quantities, and inventory data. - A record of resolving shortages and supplier issues while keeping engineering and manufacturing informed of realistic options. ## Nice to Have - Experience with camera modules, RF components, embedded compute, precision optics, or robotics hardware. - Relationships with authorized distributors, component manufacturers, or electronics manufacturing partners. - Experience with ERP/MRP and PLM systems, costed BOMs, new product introduction, or counterfeit-part prevention. --- # Supply Chain Operations & Trade Compliance Lead Canonical page: https://efference.ai/careers/supply-chain-operations-trade-compliance-lead/ Supply Chain Operations & Trade Compliance Lead at Efference. San Francisco · Full time · On-site. You'll manage the movement of Efference components and finished products between suppliers, manufacturing partners, our team, and customers. You'll manage the movement of Efference components and finished products between suppliers, manufacturing partners, our team, and customers. You'll own logistics and the trade-compliance processes behind those shipments, keeping delivery commitments and records accurate as international activity grows. ## What you’ll do - Coordinate inbound and outbound shipments, freight forwarders, customs brokers, carriers, and delivery schedules for prototypes, production parts, and customer equipment. - Maintain shipping documentation, tariff classifications, country-of-origin records, and export-control determinations with engineering input and qualified advisers where needed. - Run screening and shipment-review processes, identify licensing or documentation questions early, and resolve exceptions before goods move. - Own receiving, inventory movements, kitting, dispatch, and returns workflows, maintaining serial, lot, location, and condition records with operations and software teams. - Develop packaging and handling requirements for cameras and electronics, manage damage or loss claims, and improve transit time and landed cost. - Maintain auditable procedures and broker performance records; coordinate product-certification documents with engineering owners when required for shipment or market entry. ## What we are looking for - Experience managing international logistics and import/export operations for electronic or manufactured products. - Working knowledge of customs classification, origin, export controls, screening, commercial documentation, and Incoterms. - Experience working with freight forwarders, customs brokers, warehouses, and manufacturing partners to resolve shipment issues. - Strong operational discipline across inventory records, deadlines, costs, and supporting documentation. - Judgment about when a compliance question needs specialist advice, and the ability to translate that advice into a workable process. ## Nice to Have - Customs or trade-compliance credentials and experience supporting audits or regulatory inquiries. - Experience with ERP/WMS systems, serialized hardware, demonstration equipment, or international repair and return flows. - Experience coordinating radio and electronics certification records or special handling requirements for sensitive equipment. --- # Systems Test Engineer, End-to-End Validation Canonical page: https://efference.ai/careers/systems-test-engineer-end-to-end-validation/ Systems Test Engineer, End-to-End Validation at Efference. San Francisco · Full time · On-site. You'll validate Efference as a complete system, from image capture through network transport to GPU inference and the return path. You'll validate Efference as a complete system, from image capture through network transport to GPU inference and the return path. You'll build automated tests that expose integration failures, quantify operating limits, and give the team clear evidence for release decisions. ## What you’ll do - Define system acceptance tests with engineering owners, covering observation integrity, synchronization, delivery latency, jitter, throughput, and recovery. - Build hardware-in-the-loop rigs that combine cameras, client devices, access points, network impairment, and inference workloads in reproducible configurations. - Instrument timing from exposure to inference response, validating clock alignment and measurement uncertainty before comparing latency across hosts. - Exercise fleet load, roaming, congestion, packet loss, clock drift, thermal throttling, process crashes, and interrupted updates through stress and endurance tests. - Correlate device logs, packet traces, and GPU metrics to isolate failures; create minimal reproductions and regression tests with subsystem engineers. - Maintain a release matrix across hardware, firmware, SDK, and model-serving versions, reporting coverage, results, unresolved defects, and readiness against agreed criteria. ## What we are looking for - Experience validating complex systems that combine hardware, embedded software, networking, or distributed compute. - Strong Python skills and experience building reliable automated test infrastructure rather than only executing manual test plans. - Ability to design meaningful load and fault-injection experiments and interpret latency distributions and failure rates. - Practical debugging across Linux devices and networked services, using logs, traces, packet captures, and lab instruments. - Careful measurement practice and clear communication of what a test demonstrates, what remains untested, and why a release fails a requirement. ## Nice to Have - Experience with camera timing, PTP, hardware timestamping, network emulation, or GPU inference systems. - Work on robotics hardware-in-the-loop testing, fleet-scale simulation, or long-duration reliability tests. - Experience designing CI systems that control physical equipment and preserve complete test artifacts. --- # Hardware Test Engineer, Reliability & Manufacturing Canonical page: https://efference.ai/careers/hardware-test-engineer-reliability-manufacturing/ Hardware Test Engineer, Reliability & Manufacturing at Efference. San Francisco · Full time · On-site. You'll develop the tests that establish whether Efference hardware meets its requirements and whether each manufactured unit is ready to ship. You'll develop the tests that establish whether Efference hardware meets its requirements and whether each manufactured unit is ready to ship. You'll work across development reliability testing and production test, translating failure mechanisms into better designs, fixtures, and acceptance limits. ## What you’ll do - Create validation plans for boards and assembled devices covering power, thermal behavior, interfaces, sensors, and the operating conditions defined for each product. - Design and automate test fixtures with programmable supplies, loads, data acquisition, interface boards, and device-control software. - Run temperature, humidity, vibration, shock, power-cycle, and endurance testing as appropriate to the product, recording exposure and failure evidence. - Develop production tests for programming, calibration verification, connectivity, and functional performance with the RF, camera, and manufacturing teams. - Validate measurement repeatability, fixture correlation, and test limits so stations detect real defects without unnecessary false failures or excessive cycle time. - Investigate failures from validation, production, and returns; maintain traceable results and verify corrective actions with design engineers and suppliers. ## What we are looking for - Experience developing hardware validation, reliability, or manufacturing tests for electronic products. - Strong electrical fundamentals and practical skill with schematics, oscilloscopes, power supplies, loads, and data-acquisition equipment. - Proficiency in Python or a comparable test-automation language and experience controlling instruments and devices programmatically. - Understanding of failure analysis, measurement uncertainty, repeatability, and the difference between design qualification and production screening. - Experience working with technicians, manufacturers, and design engineers to deploy test equipment and resolve recurring failures. ## Nice to Have - Experience testing cameras, RF devices, embedded compute, or robotics electronics. - Work on fixture PCB design, boundary scan, environmental chambers, accelerated testing, or EMC pre-compliance. - Experience with statistical test-limit development, gauge repeatability studies, MES integration, or contract-manufacturer test deployment.