Perception Engineer — 3D Representation & Navigation in Irvine, California at FieldAI

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.

• Experience validating perception systems for autonomous vehicles, mobile robots, drones, industrial robots, or defense robotics platforms.

• Familiarity with perception workflows such as detection, tracking, localization, mapping, or sensor fusion.

• Experience with simulation, software-in-the-loop, hardware-in-the-loop, and replay-based validation.

• Experience with sensor calibration, synchronization, time alignment, and sensor health monitoring.

• Experience building automated regression tools or validation infrastructure.

• Familiarity with annotated datasets, ground-truth generation, and scenario-based test design.

• Knowledge of structured verification processes, requirements traceability, and safety-oriented development practices.