Robotics Software Engineer, Infrastructure

About the company

Efference provides high-performance perception and compute infrastructure for training and deploying robot models in the cloud. Our vision is to make robotic deployments scalable with shared compute.

We approach the problem by owning the entire path from the image sensor to the datacenter GPU. We shrink the load at the sensor, fix the uplink so robot traffic is fast and reliable, and clock synchronize the system so observations arrive time-aligned, ready for inference.

About the role

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.