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Salary
$100k – $230k per year
Location
In office (Irvine)
Seniority
Junior · 2+ years exp
Visa
H-1B filings in 12 months: 37 · for this role: 31
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 5, 2026. First seen by Alion on Sep 5, 2026. FieldAI scores B on the Alion truth index.

Overview
Company
Impact
Profile match
FieldAI is a robotics company that builds embodied AI and autonomy software, marketed as a general-purpose robot brain, that lets mobile robots operate safely in unstructured real-world environments, headquartered in Irvine, California. Founded in 2023 by a team with backgrounds at NASA JPL, DeepMind, Tesla, NVIDIA and Amazon, it reports production deployments on three continents for customers in construction, energy, manufacturing, mining and federal markets. Its openings are mostly for robotics autonomy, perception and mapping engineers, machine learning and ML platform engineers, embedded, electrical and mechanical hardware engineers and infrastructure software roles.

About the Job

    Field AI is building the future of autonomy-from rugged terrain to real-world deployment. We’re on a mission to develop intelligent, adaptable robotic systems that operate beyond simulation and thrive in unpredictable environments. As our Robotics Autonomy Engineer - Safety, you’ll own and advance the independent safety layer that keeps our robots safe around people, equipment, and terrain no matter what the rest of the autonomy stack decides. You’ll be part of a deeply technical team advancing real-world robotic capabilities through cutting-edge research, simulation tools, and field validation. If building the guarantees that let robots earn trust in the real world excites you, and you want to work where your code hits the ground (literally)-this is your role. This is Field AI.

What You’ll Get To Do

    • Own and evolve the safety layer that runs independently of perception, planning, and learned policies, and extend it to new wheeled, legged, and humanoid platforms
    • Build runtime monitors and collision avoidance backstops that check every commanded motion against the environment before it reaches the robot
    • Enforce speed, zone, terrain, and proximity limits, and define the safe operating envelope for each platform and deployment
    • Design fallback and minimal risk behaviors, from graceful slow down to safe stop, and the logic that decides when to trigger them
    • Build watchdogs and health monitoring across sensors, compute, communication, and actuation, so the robot always knows when it can trust itself
    • Lead hazard analysis and safety case development for new platforms and new deployments
    • Verify the safety layer in simulation, hardware-in-the-loop (HIL) testing, and field trials, with coverage that grows with every deployment
    • Work with planning, control, locomotion, and integration teams so the nominal stack plans and moves within the safety envelope

What You Have

    • Master’s degree or higher in Robotics, Computer Science, Electrical Engineering, or a related field, or a Bachelor’s degree with substantial hands-on experience on safety related autonomous systems
    • 2+ years of experience developing safety, monitoring, or fallback systems for robots or autonomous vehicles
    • Strong grounding in classical planning and control, such as collision checking and trajectory validation
    • Experience writing deterministic, real time, resource bounded C++ for systems where correctness matters more than features
    • Solid Python skills for tooling, analysis, and test automation in Linux-based environments
    • A verification mindset: you think in terms of assumptions, failure modes, coverage, and evidence
    • Familiarity with safety standards for mobile robots and autonomous systems (e.g., ISO 13482, ISO 3691-4, ISO 26262)
    • Familiarity with robotics middleware such as ROS/ROS 2, and with robot sensors such as LiDAR, depth cameras, and IMUs

The Extras That Set You Apart

    • Functional safety experience in autonomous vehicles, industrial robots, or aerospace
    • Experience with runtime assurance architectures that wrap a learned or complex controller
    • Experience with formal or set based safety methods applied to real robots
    • Experience defining operational design domains and monitoring when a system is outside them
    • Experience with redundant sensing, safety rated hardware, or safety rated communication
    • Experience taking a robotic product through safety assessment or certification
    • Experience with legged or humanoid platforms, where balance and contact make safety envelopes harder to define
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