Sobre este puesto de Robotics Autonomy Engineer, Perception en Field Ai
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, Perception 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.
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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.
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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.
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Contribute to code quality, testing, and long-term maintainability of perception systems.
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Develop tools, metrics, and tests to monitor performance and catch regressions over time.
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Help scale perception solutions across multiple robots, environments, and missions.
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Work closely with engineers, researchers, and operators to define perception requirements and deliver reliable solutions.
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Communicate technical designs, tradeoffs, and results clearly to both technical and non-technical stakeholders.
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Support field operations and customer demonstrations by ensuring perception systems are production-ready.
2. Develop and Integrate Sensor-Based Perception
3. Deploy Perception Software on Real Robots
4. Improve System Robustness and Scalability
5. Collaborate Across Teams
What You Have
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PhD degree in Robotics, Computer Science, Electrical Engineering, or a related field or MS degree in a related field with 2+ years of industry or applied research experience, or BS degree in a related field with 4+ years of relevant experience.
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Strong background in robot perception, localization, and mapping (SLAM) for real-world robotic systems.
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Hands-on experience developing and deploying perception software in field robotics environments (not just simulation).
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Proficiency in modern robotics software development (C++, Python) and ROS/ROS2 based systems.
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Experience working with robot perception and state estimation (VIO, LIO, mapping, sensor fusion etc.).
Ability to take ownership of complex subsystems, from design through field deployment and long-term maintenance. -
Comfort working close to hardware, including debugging sensor data, calibration, and real-world failures.
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Strong problem-solving skills and ability to operate independently in fast-moving, small teams.
The Extras That Set You Apart
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Experience with thermal, LWIR, or multispectral passive sensing for robotic perception.
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Experience integrating and calibrating custom sensor rigs (e.g., stereo, thermal, or multi-LiDAR setups).
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Familiarity with CI/CD pipelines, performance regression testing, and benchmarking for perception systems.
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Experience aligning or unifying perception stacks across multiple platforms or product lines.
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Demonstrated leadership in research, field operations, or mentoring junior engineers and researchers.
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Knowledge of containerization (Docker, Kubernetes) and modern DevOps practices.
