- 3+ years of experience in an industry or startup robotics setting
- Experience optimizing and deploying learning based controllers on resource constrained robotic platforms (ONNX Runtime, NVIDIA TensorRT, real time onboard inference)
- Publications or open-source contributions in locomotion, reinforcement learning, or control (e.g., CoRL, RSS, ICRA, IROS)
- Familiarity with ROS/ROS2 or custom middleware for real-time control
- Background in manipulation, loco-manipulation, or whole-body coordination
- Experience combining learned policies with model predictive control (MPC) or whole-body controllers
- Experience with motion imitation pipelines from motion capture or teleoperation data
- Experience debugging sim-to-real issues at scale
- Contributions to reinforcement learning libraries or simulation platforms
- Prior work on multi-agent learning or terrain-adaptive control systems
Our salary range is generous and we consider each individual’s background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.
Why Join FieldAI in Irvine?
In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics’ hardest challenges: reliable deployment outside the lab. Our Field Foundational Models™ raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use.
You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments.