Senior / Staff Sim-to-Real Engineer (Tendon-based Robotic Hands)

Apptronik • Austin, TX

9d

About The Position

Apptronik is seeking an experienced, autonomous Senior or Staff Sim-to-Real Engineer to bridge simulation and physical hardware for advanced tendon-driven robotic hands. The role focuses on developing efficient, accurate simulation abstractions for tendon mechanisms with complex routing, friction, elasticity, and nonlinear transmission dynamics, and validating those abstractions through empirical testing and system identification.

The engineer will help ensure that reinforcement learning policies trained in simulation transfer successfully to physical hardware. They will define system-identification roadmaps and testing protocols, characterize actuators, calibrate multi-body hand systems, and work with the RL and Controls teams on the dynamics engine and domain-randomization strategies. The role includes identifying sim-to-real bottlenecks and leading technical solutions through deployment on hardware.

Requirements

• At least 5 years of post-graduation industry or development experience in robotics, controls, or physical simulation for the Senior-level profile.
• Proven experience transferring reinforcement-learning-based control policies from simulation to physical hardware.
• Hands-on experience with control, system identification, and characterization of Quasi-Direct Drive (QDD) actuators.
• Strong foundation in rigid multi-body dynamics, kinematic calibration, and inertial identification.
• Experience verifying effort production, characterizing friction and backlash, and diagnosing hardware-software discrepancies in complex mechanisms.
• Ability to independently investigate open-ended sim-to-real problems, design empirical tests, update simulation models, and resolve reality gaps.
• For Senior Engineer: BS, MS, or PhD in Robotics, Electrical Engineering, Mechanical Engineering, Computer Science, or a related field. Experience requirements are 5+ years with a BS, 3+ years with an MS, or 1–2 years with a PhD.
• For Staff Engineer: MS or PhD in Robotics, Electrical Engineering, Mechanical Engineering, Computer Science, or a related field. Experience requirements are 10+ years with a BS, 8+ years with an MS, or 6+ years with a PhD.

Nice To Haves

• Experience in locomotion or whole-body control.
• Experience modeling, calibrating, or controlling tendon-driven or cable-driven robotic systems.
• Familiarity with modern reinforcement-learning environments and physics simulators such as MuJoCo, Isaac Sim/Gym, Drake, or Bullet.
• Experience with sim-to-real techniques such as domain randomization, system-identification-based digital twins, or actuator-net modeling.

Responsibilities

• Develop computationally efficient and accurate simulation abstractions for complex tendon-driven mechanisms.
• Design and execute empirical tests to identify system parameters and validate simulation abstractions against physical hardware.
• Perform system identification and control tuning on low-friction robotic actuators to establish high-fidelity torque and effort mapping.
• Conduct kinematic calibration, inertial parameter identification, and effort-production verification across multi-body hand systems.
• Collaborate with RL and Controls teams to support transfer of control policies from simulation to physical hardware, including zero-shot or few-shot transfer.
• Identify sim-to-real pipeline bottlenecks, propose solutions, and lead technical execution from concept through hardware deployment.
• Establish system-identification roadmaps, testing protocols, and sim-to-real engineering practices.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior