Robotics Autonomy Engineer, Systems

About the role

FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.

About the Job

At FieldAI, we’re building autonomy for robots that operate in the real world, in harsh environments, and under challenging conditions where traditional sensing breaks down. We’re looking for a Robotics Autonomy Engineer, Systems to own and advance perception capabilities for our federal autonomy programs. In this role, you will lead development of the perception stack for robots operating in unstructured terrains, taking responsibility for performance, robustness, and deployment on new platforms and sensor configurations. You’ll work hands-on across software and hardware for integrating LiDAR, RADAR and multispectral, and sensing into production autonomy systems and delivering capabilities that directly support customers.

What You Will Do 1. Build and Maintain Perception Systems

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Design, implement, and maintain perception systems for autonomous robots operating in real-world environments.

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Develop robust localization and mapping capabilities that perform reliably in unstructured, off-road, and field conditions.

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Continuously evaluate and improve perception performance through testing, iteration, and field validation.

2. Develop and Integrate Sensor-Based Perception

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Implement perception algorithms that fuse data from multiple sensors such as LiDAR, cameras, RADAR and inertial sensors.

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Support the integration of new sensing modalities and sensor configurations as robotic platforms evolve.

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Ensure perception software operates reliably across simulation and real-world deployments.

3. Deploy Perception Software on Real Robots

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Bring perception algorithms from development to deployment on physical robotic systems.

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Debug and resolve issues discovered during on-robot testing and field operations.

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Collaborate with autonomy, controls, and platform teams to ensure perception systems integrate cleanly into the full autonomy stack.

4. Improve System Robustness and Scalability

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Contribute to code quality, testing, and long-term maintainability of perception systems.

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