Senior/Staff Autonomy Software Generalist

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.