Senior Controls Engineer (Federal)

FieldAI

$70K — $200K *
Aerospace & Defense
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Ph.D. or MS in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, or a related field, with focus on planning or controls.
  • Deep expertise in modern control theory, specifically predictive and sampling-based control methodologies.
  • Proven experience deploying complex control algorithms onto physical robots.
  • Experience with large-scale or off-road autonomous vehicles in unstructured environments.
  • Strong design skills for computationally constrained control schemes.
  • Ability to debug complex control architectures and adapt software to new platforms.
  • Proficiency in C++, Python, CUDA, ROS1/2, Docker, Linux.

Responsibilities

  • Lead the design and implementation of control systems for autonomous vehicles.
  • Evaluate and implement advanced control schemes for various vehicle architectures.
  • Develop robust control stacks for safe operations across the robotic fleet.
  • Design low-latency safety behaviors for vehicles in unstructured environments.
  • Deploy control schemes and behaviors onto real-world robots under demanding conditions.
  • Act as the technical expert for planning and controls, guiding team strategy.
  • Oversee the generalization of controller systems for efficient robot integration.

Benefits

  • Health, dental, and vision insurance.
  • Equity participation.
  • Flexible working hours and generous paid time off.
  • Opportunities for professional development and training.
  • Supportive work environment fostering innovation and collaboration.
Full Job Description
About the Job

At FieldAI, we build autonomous robotic systems that operate in demanding, real-world environments where tight integration between hardware and software is critical. We're looking for a Senior Robotics Engineer to lead the design, implementation, and deployment of advanced control systems and collaborative behaviors for our autonomous vehicle fleet. In this role, you will serve as a key planning and controls expert, solving complex challenges involving operating in unstructured environments. You will own the evaluation and implementation of advanced control schemes, ensuring computationally constrained systems operate reliably across new and existing robotic platforms. Furthermore, you will drive the development of the controller level safety layer for safe robot operations. This is a highly impactful role for an engineer with deep expertise in control theory and robot safety who can translate advanced research into robust, field-ready solutions.
1. Vehicle Planning and Control
  • Identify and model the dynamic behavior of autonomous vehicles to establish accurate baselines for motion planning.
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  • Adapt and train control models to transition between diverse vehicle platforms.
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  • Develop, optimize, and implement robust control stacks across the fleet to ensure safe and reliable operations.
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2. Advanced Controller Design and Implementation
  • Evaluate advanced control schemes for varying vehicle architectures.
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  • Design and implement computationally efficient control and planning algorithms tailored to the hardware and compute limitations.
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  • Verify and validate new control schemes directly on physical robots, overcoming bottlenecks when porting controllers to new platforms.
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3. Robot Safety
  • Lead architectural design discussions for controller level safety layer
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  • Develop and implement robust low-latency safety behaviors for our vehicle fleets operating in unstructured environments.
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  • Execute, test, and deploy multi-agent behaviors to ensure the timely delivery of capabilities for key customer milestones.
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4. Field Robotics Integration and Testing
  • Deploy theoretical control schemes and multi-agent behaviors onto real-world robots operating in demanding, dynamic environments.
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  • Leverage deep domain expertise in off-road field robotics to ensure software robustness against unpredictable terrain and environmental conditions.
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  • Bridge the gap between advanced multi-agent research and practical, reliable product development for real-world deployments.
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5. Technical Leadership and System Scalability
  • Serve as a resident planning and controls expert, filling critical knowledge gaps and guiding technical strategy for the engineering team.
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  • Lead the effort to generalize highly specific robot controllers, ensuring new robots can be brought online quickly and efficiently.
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  • Ensure the timely delivery of critical autonomy capabilities to fulfill broader company goals, operational promises, and customer contracts.
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What You Have
  • 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.
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  • Deep expertise in modern control theory, specifically with predictive and sampling-based control methodologies (such as MPC and MPPI), and vehicle dynamics modeling.
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  • Proven experience deploying complex control and planning algorithms onto physical robots, rather than just in simulation.
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  • Experience working with large-scale or off-road autonomous vehicles operating in unstructured, real-world environments.
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  • Strong ability to design and implement computationally constrained control schemes tailored to the compute limitations of embedded robotic platforms.
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  • Ability to verify, validate, and debug complex control architectures, overcoming system-level bottlenecks when adapting software to new vehicle platforms.
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  • Strong ownership mindset with the ability to serve as a resident technical expert, bridging the gap between advanced autonomy research and reliable product deployment.
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  • Hands-on experience with C++, Python, CUDA. ROS1/2, Docker, Linux
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The Extras That Set You Apart
  • Experience with field robotics, off-road vehicles, or high-speed / safety-critical robotic systems.
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  • Background in control theory, including classical and learning-based controllers.
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  • Experience with low SWaP (Size, Weight, and Power) robotic platforms.
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  • Prior ownership of system integration or technical leadership for a robotic platform.
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  • Experience mentoring junior engineers or leading integration efforts in small teams.
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  • Familiarity with autonomy stacks, planning systems, or real-time robotics software architectures.
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  • Knowledge of containerization ( Kubernetes) and modern DevOps practices.
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Compensation

The salary range for this role is $70,000-$200,000. The actual offer for this position will be based on factors such as relevant experience, competencies, certifications, and how well the candidate meets the qualifications outlined above. Part of our compensation package also includes full benefits, equity, and generous time.

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