We’re looking for an autonomy software generalist to work across the full robotics stack — perception, localization, mapping, and planning — while collaborating closely with hardware, firmware, applications, and operations teams. This is a broad role suited to someone who thrives on solving problems end-to-end, from algorithm design to fleet-scale deployment, and who stays energized by the fast pace of advances in robotics and AI.
Responsibilities
- Design, implement, tune, and improve path and motion planning algorithms for safe, smooth, and continuous robot motion in large-scale, dynamic environments.
- Develop perception algorithms using both deep learning and classical geometric computer vision.
- Implement, tune, and maintain localization and mapping (SLAM) algorithms, applying state-of-the-art ML approaches where they add value.
- Perform sensor selection and evaluation across lidar, cameras, and ToF sensors, balancing performance against cost and other constraints.
- Develop and maintain calibration algorithms for the above sensors.
- Help shape the autonomy roadmap by identifying technical gaps and risks, proposing prioritized initiatives, and translating them into milestones
- Build tooling and metrics to test, evaluate, and continuously improve fleet performance, including regression detection and proactive service triggers.
- Own high-quality software engineering practices: version control (GitHub), code review, CI/CD, and maintaining build and deployment pipelines.
- Work cross-functionally with hardware, firmware, applications, and operations teams to develop, ship, and scale new products.
Requirements
- Master’s degree in Robotics, Computer Science, or a related field (or equivalent experience).
4 or more years developing production robotics or autonomy software.
Strong proficiency in ROS, C++ and Python in a Linux environment.
Hands-on experience implementing and tuning algorithms in two or more of: perception, path/motion planning, localization/mapping, sensor calibration.
Experience with deploying deep learning models
Solid software engineering fundamentals: Git, code review, CI/CD, and build pipeline maintenance.
Practical experience working with real sensor data from lidar, cameras, and/or ToF sensors.
Demonstrated ability to work cross-functionally and ship to real hardware.
Nice to Haves
Familiarity with cutting-edge ML approaches to localization, mapping, and perception (e.g., object detection and tracking, learned features, visual place recognition).
Experience with cloud-based or collaborative/lifelong SLAM systems.
Experience with containerization and deployment tooling
A track record of staying current with robotics and AI research and bringing new ideas into practice.
Why Join Relay Robotics?
Compensation
Compensation: Based on experience and qualifications.
Relay Robotics Campbell, California, USA Office
271 E. Hacienda Avenue, Campbell, CA, United States, 95008
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