Senior / Staff Sim-to-Real Engineer

The role

This person will bridge the gap between simulation and physical hardware for advanced tendon-driven robotic hands. They will create accurate physical abstractions for simulators and ensure Reinforcement Learning policies transfer to physical hardware.

What you will do

• Develop and implement physical abstractions for tendon-driven mechanisms in simulation.
• Design and execute empirical testing protocols to identify system parameters.
• Perform system ID and control tuning on low friction robotic actuators.
• Drive kinematic calibration, inertial parameter identification, and effort production verification.
• Collaborate with RL and Controls teams to support transfer of control policies onto hardware.
• Identify bottlenecks in the sim-to-real pipeline and lead technical execution.

Required qualifications

• Senior Engineer: BS, MS or PhD in Robotics, Electrical Engineering, Mechanical Engineering, Computer Science, or a related field.
• Senior Engineer: 5+ years of relevant industry experience 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.
• Staff Engineer: 10+ years of relevant industry experience with a BS, 8+ years with an MS, or 6+ years with a PhD.
• Proven track record of transferring RL-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/backlash, and diagnosing hardware-software discrepancies.
• Ability to design empirical tests and update simulation models independently.
• Prolonged periods of sitting at a desk and working on a computer.
• Must be able to lift 15 pounds at times.
• Vision to read printed materials and a computer screen.

Nice to have

• Experience in locomotion or whole-body control
• Specific experience modeling, calibrating, or controlling tendon-driven or cable-driven robotic systems.
• Familiarity with modern RL environments and physics simulators (e.g., MuJoCo, Isaac Sim/Gym, Drake, or Bullet).
• Experience with sim-to-real techniques such as Domain Randomization, System ID-based digital twins, or Actuator Net modeling.

About the company

Apptronik is a human-centered robotics company developing AI-powered robots to support humanity. Their flagship humanoid robot, Apollo, is built to collaborate with people in industries such as manufacturing and logistics.