Robotics Software Engineer — Dexterous Manipulation

Apptronik; Mountain View (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Apptronik in Austin, TX seeks a Software Engineer focused on Dexterous Manipulation to advance RL-based control for high-DOF robotic hands. You will translate cutting-edge research into production software that runs in simulation and on real robots, collaborating across simulation, hardware, and systems teams.

You will apply knowledge of reinforcement learning, domain randomization, and real-time controls to deliver robust manipulation capabilities on hardware while maintaining code quality and

Qualifications

• Dexterous manipulation experience with multi-fingered hands and high-DOF control.
• Proficiency in reinforcement learning for robotic control and familiarity with imitation learning.
• Strong programming skills in Python and C++ for real-time robotic software.

Responsibilities

• Implement and tune control algorithms for multi-fingered hands and tactile feedback integration.
• Develop and maintain low-latency manipulation software inside real-time control stacks.
• Build and refine sim-to-real pipelines and validate in simulation and on hardware.

Skills

Dexterous manipulation

Reinforcement learning

Python

C++

Sim-to-real

Real-time robotics

Kinematics & dynamics

Computer vision

Education

BS/MS/PhD in Robotics/CS/EE

Tools

IsaacSim

MuJoCo

Drake

Job description

Apptronik in Austin, TX seeks a Software Engineer focused on Dexterous Manipulation to advance RL-based control for high-DOF robotic hands. You will translate cutting-edge research into production software that runs in simulation and on real robots, collaborating across simulation, hardware, and systems teams.

You will apply knowledge of reinforcement learning, domain randomization, and real-time controls to deliver robust manipulation capabilities on hardware while maintaining code quality and