# 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.