Robotics Control Engineer - Whole Body Control

XDOF • San Francisco, CA

3d

About The Position

At XDOF, we're at an inflection point. Frontier labs are racing to build general-purpose robots, and high-quality training data is the bottleneck. We're building the foundation behind the foundation models — the data collection systems, operational capability, exabyte-scale data warehouse, and software toolchain — to help our partners drive the field forward. Great data starts with great hardware behavior. We're looking for a Robotics Controls Engineer to build the high-performance control systems that make our dexterous manipulators and humanoid robots move safely, precisely, and repeatably — because every teleoperation session, every collection run, and every downstream model depends on robots that respond exactly as commanded.

Requirements

• bachelor's or master's degree (or equivalent experience) in robotics, mechanical engineering, electrical engineering, computer science, or a related field
• strong fundamentals in robot dynamics, kinematics, and feedback control
• hands-on experience implementing controllers on real robotic systems, not just in simulation
• strong C++ and/or Python, and comfort working with real-time robotics systems

Nice To Haves

• experience with whole-body control, operational-space control, MPC, or optimization-based control
• come from a background in humanoid robotics, manipulation, legged robotics, or advanced industrial robot control
• worked on real-time embedded control software and understand the constraints of deploying to physical hardware
• very comfortable working in 0→1 environments
• mission-driven and passionate about robotics: work at XDOF is fast-paced and constant. We hope you love what you're going to be doing, because you'll be doing a lot of it!

Responsibilities

• implementing joint-space and Cartesian impedance / torque control for 7+ DoF robotic arms
• building whole-body control (WBC) for highly redundant humanoids with mobile bases, arms, and actuated torsos
• designing optimization-based controllers: QP formulations, inverse dynamics, task/null-space control, and redundancy resolution
• developing collision-aware motion and control, including self-collision avoidance and environment constraints
• implementing and integrating real-time control software on physical robots, from simulation through hardware deployment
• tuning and validating controller performance across diverse manipulation and locomotion tasks
• working closely with data collection operators and hardware teams to diagnose and resolve control-related failure modes during teleoperation and autonomous runs

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Associate degree