Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. Our flagship humanoid robot, Apollo, is built to collaborate thoughtfully with people, starting with critical industries such as manufacturing and logistics, with future applications in healthcare, the home, and beyond.

We operate at the cutting edge of Applied AI, applying our expertise across the full robotics stack to solve some of society's most important problems. You will join a team dedicated to bringing Apollo to market at scale, tackling the complex challenges like safety, commercialization, and mass production to change the world for the better.

JOB SUMMARY

We are looking for an experienced and autonomous Senior/Staff Sim-to-Real Engineer to bridge the gap between simulation and physical hardware for our advanced tendon-driven robotic hands.

Simulating tendon-driven mechanisms is notoriously difficult due to complex routing, friction, elasticity, and non-linear transmission dynamics. In this role, you will be responsible for creating elegant, highly accurate abstractions of these complex mechanisms for our simulators, and proving they work through rigorous empirical testing and system identification.

You will play a critical role in our control pipeline, ensuring that Reinforcement Learning (RL) policies trained in simulation successfully transfer to physical hardware. As a senior member of the team, you will have the autonomy to define our system identification roadmap, establish testing protocols, and drive the sim-to-real engineering culture.

ESSENTIAL DUTIES AND RESPONSIBILITIES or KEY ACCOUNTABILITIES

• Tendon Mechanism Abstraction: Develop and implement simple, computationally efficient, and highly accurate physical abstractions for complex tendon-driven mechanisms in simulation.
• System Identification & Validation: Design and execute empirical testing protocols to identify system parameters and prove that your simulation abstractions accurately reflect physical reality.
• Actuator Characterization: Perform rigorous system ID and control tuning on low friction robotic actuators to ensure high-fidelity torque and effort mapping.
• Rigid Multi-Body Calibration: Drive the kinematic calibration, inertial parameter identification, and effort production verification across our multi-body hand systems.
• Sim-to-Real Pipeline Ownership: Collaborate closely with the RL and Controls teams to ensure the dynamics engine and domain randomization strategies perfectly support zero-shot or few-shot transfer of control policies onto physical hardware.
• Technical Leadership: Operate autonomously to identify bottlenecks in the sim-to-real pipeline, propose solutions, and lead the technical execution from concept to deployed hardware.