Senior Perception Engineer

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.

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

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

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

Develop and Integrate Sensor-Based Perception -Implement perception algorithms that fuse data from multiple sensors such as LiDAR, cameras, RADAR and inertial sensors.

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

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

Deploy Perception Software on Real Robots -Bring perception algorithms from development to deployment on physical robotic systems.

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

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

Improve System Robustness and Scalability -Contribute to code quality, testing, and long-term maintainability of perception systems.

-Develop tools, metrics, and tests to monitor performance and catch regressions over time.

-Help scale perception solutions across multiple robots, environments, and missions.

Collaborate Across Teams

        -Work closely with engineers, researchers, and operators to define perception requirements and deliver reliable solutions.

        -Communicate technical designs, tradeoffs, and results clearly to both technical and non-technical stakeholders.

        -Support field operations and customer demonstrations by ensuring perception systems are production-ready.

Bachelor’s degree in Computer Science, Robotics, Machine Learning, or a related technical field; graduate degree preferred.

4+ years of professional experience in machine learning, computer vision, robotics, or related areas, with substantial hands-on perception engineering experience.

Hands-on experience deploying perception systems on real-world robotic platforms; experience limited to simulation or offline datasets is not sufficient.

Strong experience working with LiDAR and vision sensors, particularly for 3D perception and real-world robotics applications.

Strong systems-level understanding of perception and its interaction with the broader autonomy stack, with the ability to reason about interfaces, latency, failure modes, and downstream behavior.

Experience with planning, navigation, or controls is a strong plus, especially where perception outputs directly influence robot behavior.

Experience debugging systems, including sensor data quality, synchronization, calibration, coordinate transforms, and failures observed only during real-world operation.

Ability to own complex perception subsystems end-to-end—from technical design and implementation through deployment, validation, debugging, and long-term maintenance.

Strong software engineering fundamentals and experience writing robust, production-quality C++.

Experience with CUDA and GPU optimization is highly desirable.

Background in autonomous vehicles, field robotics, mobile robotics, or similarly complex real-world autonomous systems.

Ability to operate effectively across algorithm, systems, and product boundaries and collaborate closely with perception, platform, planning, and field engineering teams.

• Experience with thermal, LWIR, or multispectral passive sensing for robotic perception. • Experience integrating and calibrating custom sensor rigs (e.g., stereo, thermal, or multi-LiDAR setups). • Familiarity with CI/CD pipelines, performance regression testing, and benchmarking for perception systems. • Experience aligning or unifying perception stacks across multiple platforms or product lines. • Demonstrated leadership in research, field operations, or mentoring junior engineers and researchers. • Knowledge of containerization (Docker, Kubernetes) and modern DevOps practices.

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