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

Apptronik • Austin, TX

8d

About The Position

Apptronik is seeking an experienced, autonomous Senior/Staff Sim-to-Real Engineer to bridge the gap between simulation and physical hardware for its tendon-driven robotic hands. The role focuses on developing efficient, accurate simulation abstractions for complex tendon mechanisms involving routing, friction, elasticity, and nonlinear transmission dynamics, then validating those abstractions through empirical testing and system identification. The engineer will help ensure reinforcement learning policies trained in simulation transfer successfully to physical hardware.

As a senior team member, this person will define the system identification roadmap, establish testing protocols, and advance the sim-to-real engineering culture. They will work closely with Reinforcement Learning and Controls teams and lead technical work from problem identification through deployment on hardware.

The position requires at least five years of relevant post-graduation experience for the Senior level, with different education and experience combinations specified for Senior and Staff candidates. This is a direct-hire position. The job description also states that Apptronik provides equal employment opportunities and prohibits discrimination and harassment.

Requirements

• At least 5 years of post-graduation industry or development experience in robotics, controls, or physical simulation for the Senior/Staff role.
• A proven track record of 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.
• Demonstrated ability to independently investigate open-ended technical problems, design empirical tests, update simulation models, and resolve the reality gap.
• Senior Engineer: BS, MS, or PhD in Robotics, Electrical Engineering, Mechanical Engineering, Computer Science, or a related field. Experience requirement: 5+ years with a BS, 3+ years with an MS, or 1–2 years with a PhD.
• Staff Engineer: MS or PhD in Robotics, Electrical Engineering, Mechanical Engineering, Computer Science, or a related field. Experience requirement: 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 and implement simple, computationally efficient, accurate physical abstractions for complex tendon-driven mechanisms in simulation.
• Design and execute empirical testing protocols to identify system parameters and validate simulation abstractions against physical reality.
• Perform system identification and control tuning on low-friction robotic actuators to ensure high-fidelity torque and effort mapping.
• Conduct kinematic calibration, inertial parameter identification, and effort production verification across multi-body hand systems.
• Collaborate with Reinforcement Learning and Controls teams to ensure the dynamics engine and domain randomization strategies support zero-shot or few-shot transfer of control policies to physical hardware.
• Identify bottlenecks in the sim-to-real pipeline, propose solutions, and lead technical execution from concept through deployment on hardware.
• Define the system identification roadmap, establish testing protocols, and drive the sim-to-real engineering culture.

What This Job Offers

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