Senior Robotics Control Engineer

The Role

The Senior Robotics Control Engineer will design and develop real-time control systems for advanced robotic manipulators, with a focus on torque control, motion planning, and state estimation. This role involves building optimization-based control algorithms, integrating sensor fusion across multiple sensing modalities, and driving controller performance from simulation through hardware validation.

Working closely with the Autonomy, Hardware, and Testing teams, the engineer will develop scalable, high-performance robotics solutions that enable precise, reliable, and intelligent manipulation in real-world environments.

Key Responsibilities

• Design and develop real-time C++ code control of robotic arms, with emphasis on torque control and low impedance.
• Build model-based planning and control components: trajectory optimization, inverse dynamics, and whole-arm motion control.
• Develop state estimation for real-time manipulation, fusing encoders, torque sensors, force-torque sensing, and IMUs.
• Own controller performance end-to-end: simulation validation, hardware bring-up, tuning, and regression testing.
• Design scalable solutions that integrate with Autonomy, Hardware, and Testing systems at Foundry.

What We're Looking for

• Founder mentality: We love people who build like it’s their own company.
• You move fast, take ownership, and find a way through when the path isn’t obvious.
• You have the drive to make big things happen and the judgment to take smart risks along the way.
• If you prefer a clearly defined lane, a predictable pace, and all the answers before you start, there’s nothing wrong with that-but Foundry might not be the right fit.

• 5+ years of experience implementing optimization-based multi-DOF control algorithms (inverse dynamics, trajectory optimization) on real robotic systems
• Experience building state estimation solutions for real-time robotic systems such as (E)KFs, Particle Filters, Factor Graphs, etc.
• Experience with various sensors (encoders, torque sensors, force-torque sensors, IMUs) and sensor fusion
• Deep understanding of spatial kinematics, dynamics, and related mathematical concepts
• A proven track record iterating on complex multi-DOF systems, with emphasis on torque control and low impedance
• Fluency in modern C++ and Python

Additional Qualifications

• MPC / receding-horizon control on real systems
• Contact-rich manipulation, grasping, or force-controlled assembly
• Rigid-body dynamics libraries (Pinocchio, Drake, MuJoCo) and optimization solvers
• ROS 2 and real-time Linux
• Experience with Machine Learning as it relates to control or state estimation (learned dynamics models, residual policies, imitation learning)