- Robot type
- Robot AI and Software
- Location
- IrvineCaliforniaUSA
- Job type
- Artificial Intelligence
- Posted
- Aug 27, 2026
Perception Engineer, 3D Representation & Navigation
Job description
Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence.
Job requirements
- 1. Own 3D Representation for Navigation (core focus)
- Design and build the 3D scene/traversability representations our robots plan and act on — point cloud–based or learned implicit structures — optimized for real-time, on-robot use rather than offline reconstruction quality.
- Drive a long-term research agenda on learning-based approaches to building these representations — learned traversability, learned surface/reconstruction, geometry-aware embeddings — rather than only integrating existing classical pipelines.
- Stay close to the current literature on 3D scene representation for navigation — online navigation-mesh construction from streaming point clouds, learned elevation/traversability mapping, topologically-grounded navigation representations — and translate promising ideas into deployable systems.
- 2. Build and Maintain Perception Systems
- Design, implement, and maintain perception systems for autonomous robots operating in real-world environments.
- Develop localization and mapping capabilities that hold up in unstructured, off-road, and field conditions.
- Continuously evaluate and improve perception performance through testing, iteration, and field validation.
- 3. Develop and Integrate Sensor-Based Perception
- Implement perception algorithms that fuse data from multiple sensors — LiDAR, cameras, RADAR, inertial sensors.
- Support integration of new sensing modalities and configurations as platforms evolve.
- Ensure perception software behaves consistently across simulation and real-world deployment.
- 4. Deploy Perception Software on Real Robots
- Take representations and algorithms from research prototype to production on physical robots.
- Debug issues discovered during on-robot testing and field operations.
- Collaborate with autonomy, controls, and platform teams to integrate cleanly into the full autonomy stack.
- 5. Improve System Robustness and Scalability
- Contribute to code quality, testing, and long-term maintainability.
- Build tools, metrics, and regression tests for representation quality and downstream navigation performance.
- Help scale representation and perception solutions across multiple robots, environments, and missions.
- 6. Collaborate Across Teams
- Work with engineers, researchers, and field operators to define representation and perception requirements.
- Communicate technical tradeoffs clearly to both technical and non-technical stakeholders.
- Support field operations and customer demonstrations by keeping systems production-ready.
- Bachelor’s or Master’s degree in Robotics, Electrical Engineering, Computer Engineering, Computer Science, Mechanical Engineering, or a related technical field.
- 3+ years of experience in verification, validation, systems test, or perception evaluation for robotics, autonomous systems, automotive, or similar domains.
- Experience working with robotic sensors such as LiDAR, cameras, GPS, and IMUs.
- Strong understanding of perception system behavior, sensor limitations, and common failure modes.
- Experience developing test plans, validation procedures, performance metrics, and structured test reports.
- Experience analyzing logs, datasets, and field results to debug issues and perform root-cause analysis.
- Strong cross-functional communication skills and the ability to work effectively with development teams while representing an independent V&V function.
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