Robotics Software Engineer, Dexterous Hands & RL

Perot Jain; Austin (TX); On-site; USD 120,000 - 170,000; Full time

Job summary

Apptronik is seeking a Software Engineer – Dexterous Manipulation to advance robot hands with human‑like precision. You will implement and tune RL and learning‑based control for high‑DOF hands, translating research into production code that runs in simulation and on real hardware.

You will collaborate across simulation, hardware, and systems teams to build robust manipulation capabilities, drive sim‑to‑real pipelines, and ensure reliable real‑time performance.

Qualifications

• Dexterous manipulation experience with multi-fingered hands.
• RL for robotic control including imitation learning.
• Strong Python and C++ experience for real-time systems.
• Experience with sim-to-real pipelines and validation.

Responsibilities

• Implement and tune control algorithms for multi-fingered hands.
• Develop and maintain manipulation software with low-latency execution.
• Translate RL/ imitation learning methods into production code.
• Build sim-to-real pipelines and validate in IsaacSim / MuJoCo / Drake.
• Deploy and debug manipulation capabilities on physical robots.
• Collaborate with hardware and systems engineers; ensure testing and documentation.
• Uphold code quality through rigorous testing and peer review.

Skills

Dexterous manipulation

Reinforcement learning for robotic

Python & C++ for real-time

Sim/real pipelines

Education

BS/MS/PhD in Robotics, CS, EE

Tools

IsaacSim

MuJoCo

Drake

Job description

Apptronik is seeking a Software Engineer – Dexterous Manipulation to advance robot hands with human‑like precision. You will implement and tune RL and learning‑based control for high‑DOF hands, translating research into production code that runs in simulation and on real hardware.

You will collaborate across simulation, hardware, and systems teams to build robust manipulation capabilities, drive sim‑to‑real pipelines, and ensure reliable real‑time performance.