Field AI
Robotics Autonomy Engineer, Perception
$100K–$200K
Irvine, CA +1 · On-site · Full-time · Posted Sep 16, 2026
- Location
- Irvine, CA
Peoria, Illinois - Experience
- 2+ years with an MS, or 4+ years with a BS; a PhD is also listed as an alternative.
- Education
- PhD in Robotics, Computer Science, Electrical Engineering, or a related field; or MS in a related field; or BS in a related field.
About the job
Own and develop perception systems for field robots, from sensor integration and localization to testing and deployment on physical platforms.
What you'll do
- Develop, test, and improve perception, localization, and mapping systems for unstructured field conditions.
- Integrate multisensor perception software and deploy, debug, and validate it on robots in real-world operations.
- Improve system robustness, testing, and scalability while collaborating across engineering teams and supporting field demonstrations.
What they ask for
- Strong background in robot perception, localization, and mapping (SLAM) for real-world robotic systems.
- Hands-on experience developing and deploying perception software in field robotics environments, not just simulation.
- Proficiency in C++, Python, and ROS/ROS2-based systems; experience with perception and state estimation such as VIO, LIO, mapping, or sensor fusion.
- PhD in a related field, or MS in a related field with 2+ years of industry or applied research experience, or BS in a related field with 4+ years of relevant experience.
Nice to have
- Experience with thermal, LWIR, or multispectral passive sensing, or custom sensor-rig integration and calibration.
- Familiarity with CI/CD, performance benchmarking, Docker, Kubernetes, or modern DevOps practices.
Pay
USD 100,000–200,000 (per-year-salary) — base salary
Tools
LiDAR, RADAR, C++, Python, ROS/ROS2, VIO, LIO, Docker
AI focus
Develop perception capabilities for embodied robotics, including sensor fusion, localization, and mapping for reliable field autonomy.
Model-written summary · the original posting is authoritative