Senior Controls Engineer (Federal)

FieldAI is transforming how robots interact with the real world by building advanced AI systems for robotics. They are seeking a Senior Controls Engineer to lead the design and deployment of control systems for autonomous vehicles, ensuring reliability and safety in complex environments.

Responsibilities:

• Identify and model the dynamic behavior of autonomous vehicles to establish accurate baselines for motion planning
• Adapt and train control models to transition between diverse vehicle platforms
• Develop, optimize, and implement robust control stacks across the fleet to ensure safe and reliable operations
• Evaluate advanced control schemes for varying vehicle architectures
• Design and implement computationally efficient control and planning algorithms tailored to the hardware and compute limitations
• Verify and validate new control schemes directly on physical robots, overcoming bottlenecks when porting controllers to new platforms
• Lead architectural design discussions for controller level safety layer
• Develop and implement robust low-latency safety behaviors for our vehicle fleets operating in unstructured environments
• Execute, test, and deploy multi-agent behaviors to ensure the timely delivery of capabilities for key customer milestones
• Deploy theoretical control schemes and multi-agent behaviors onto real-world robots operating in demanding, dynamic environments
• Leverage deep domain expertise in off-road field robotics to ensure software robustness against unpredictable terrain and environmental conditions
• Bridge the gap between advanced multi-agent research and practical, reliable product development for real-world deployments
• Serve as a resident planning and controls expert, filling critical knowledge gaps and guiding technical strategy for the engineering team
• Lead the effort to generalize highly specific robot controllers, ensuring new robots can be brought online quickly and efficiently
• Ensure the timely delivery of critical autonomy capabilities to fulfill broader company goals, operational promises, and customer contracts

Requirements:

• Ph.D. in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, or a related field with a focus on planning, controls, or multi-agent systems; OR an MS degree in a related field with 3+ years of relevant industry experience
• Deep expertise in modern control theory, specifically with predictive and sampling-based control methodologies (such as MPC and MPPI), and vehicle dynamics modeling
• Proven experience deploying complex control and planning algorithms onto physical robots, rather than just in simulation
• Experience working with large-scale or off-road autonomous vehicles operating in unstructured, real-world environments
• Strong ability to design and implement computationally constrained control schemes tailored to the compute limitations of embedded robotic platforms
• Ability to verify, validate, and debug complex control architectures, overcoming system-level bottlenecks when adapting software to new vehicle platforms
• Strong ownership mindset with the ability to serve as a resident technical expert, bridging the gap between advanced autonomy research and reliable product deployment
• Hands-on experience with C++, Python, CUDA. ROS1/2, Docker, Linux
• Experience with field robotics, off-road vehicles, or high-speed / safety-critical robotic systems
• Background in control theory, including classical and learning-based controllers
• Experience with low SWaP (Size, Weight, and Power) robotic platforms
• Prior ownership of system integration or technical leadership for a robotic platform
• Experience mentoring junior engineers or leading integration efforts in small teams
• Familiarity with autonomy stacks, planning systems, or real-time robotics software architectures
• Knowledge of containerization (Kubernetes) and modern DevOps practices