Field AI  is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications. 
 
 
 
 
 About the Job 
 
 
 
 
 We’re building robots that move with agility, balance, and grace in the real world—and we need a controls engineer to make that happen. You’ll own the control stack from modeling and simulation through embedded implementation on hardware. You’ll design and deploy control and estimation algorithms that power legs, arms, and whole-body behaviors for next-gen robots and humanoids. If you love turning beautiful math into real-time code that makes 100+ kg machines dance, this is your role.
What You’ll Get To Do
• Control algorithms & real-time implementation
• Design, tune, and validate controllers (classical, modern/state-space, whole-body QP, MPC) for balance, locomotion, and manipulation.
• Implement high-rate control loops (≈100–1,000 Hz+) on embedded targets (MCUs and embedded Linux) with RTOS constraints, fixed-/floating-point trade-offs, and tight timing budgets.
• Estimation & system identification
• Build and deploy filters (EKF/UKF/ESKF) for IMU/encoder/vision fusion, contact estimation, and state reconstruction.
• Perform offline/online system identification of actuators and structures; parameterize friction/backlash/COM/inertia; maintain plant models that match reality.
• Simulation, tooling, and testing
• Create fast simulations (Python/NumPy; Drake/MuJoCo/Isaac Sim as appropriate) for controller bring-up and regression testing.
• Stand up HIL rigs, logging/telemetry, and automated CI to catch issues before they hit hardware.
• Hardware integration, safety, and collaboration
• Work shoulder-to-shoulder with mech/EE/firmware/perception to integrate sensors, drivers, and actuators.
• Implement watchdogs, FDI/FDIR, and safe-state behaviors; contribute to coding standards, reviews, and documentation.
The Extras That Set You Apart
• Degree in ME/EE/Robotics/CS (BS required; MS/PhD a plus) or equivalent hands-on experience.
• Strong C/C++ and Python; comfortable writing low-level embedded code (interrupts, DMA, drivers) and performance-aware control loops.
• Deep fundamentals in mechanics, dynamics, and multi-body dynamics (rigid-body kinematics, centroidal/whole-body dynamics, spatial algebra).
• Mastery of linear & state-space control (discrete-time design, LQR/LQG, observers), frequency-domain analysis, and stability/robustness proofs.
• Practical experience with model predictive control (formulation, constraints, warm-starts) and QP/OSQP/qpOASES/acados-style solvers.
• Proficiency in Kalman filtering and multi-sensor fusion; solid grasp of observability and noise modeling.
• System identification experience (grey-box/black-box, parameter estimation, excitation design, validation).
• Embedded platforms: MCUs, embedded Linux/RT-patched kernels, and at least one RTOS.
• Comfortable with motor control and electromechanical systems (encoders, force/torque sensors); scopes/logic analyzers and hardware bring-up.
• Solid software practices: Git, code review, unit/integration testing, and reproducible experiment workflows.