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

Software Engineer - Dexterous Manipulation

Austin, TX

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

The Software Engineer – Dexterous Manipulation is a core contributor to our robots' ability to interact with the world with human-like precision. You will implement, tune, and deploy reinforcement learning and related learning-based control for high-DOF, multi-fingered robotic hands—translating state-of-the-art research (reinforcement / imitation learning, teleoperation retargeting) into reliable, production‑grade software that runs in both simulation and on physical hardware. Working across simulation, hardware, and systems teams, you will get complex manipulation tasks working robustly on real robots.

ESSENTIAL DUTIES AND RESPONSIBILITIES or KEY ACCOUNTABILITIES

• Implement and tune control algorithms for multi-fingered hands—grasping, in-hand manipulation, and tactile-feedback integration.
• Develop and maintain manipulation software with low-latency, reliable execution inside the real-time controls stack.
• Build and refine sim-to-real pipelines—hand models, domain randomization, and validation in IsaacSim / MuJoCo / Drake.
• Deploy and debug manipulation capabilities on physical robots; diagnose sensor-noise, latency, and calibration issues.
• Collaborate with hardware and systems engineers, feeding back on hand performance and sensor/actuator requirements.
• Uphold code quality through rigorous testing, documentation, and peer review.

SKILLS AND REQUIREMENTS

• Dexterous manipulation experience: multi-fingered grasping, in-hand manipulation, and high-DOF hand control.
• Reinforcement learning for robotic control—reward design, training, and debugging—ideally applied to dexterous manipulation (imitation learning and diffusion policies a plus).
• Strong Python and working C++ for real-time robotic software.
• Hands‑on experience training and validating policies in a physics simulator (IsaacSim, MuJoCo, or Drake).
• Robotics fundamentals: kinematics, dynamics, and Jacobian-based control.
• A track record of getting algorithms working on physical hardware, not simulation alone.
• Nice to have: teleoperation (VR/haptic) and retargeting, tactile-sensing integration, computer vision (6D pose / point clouds), and end‑effector bring‑up & calibration.

EDUCATION and/or EXPERIENCE

• BS/MS/PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
• 3+ years of relevant experience in robotic manipulation or complex motion control (recent PhD graduates considered).
• Evidence of taking complex algorithms from research / simulation to successful deployment on physical hardware.

PHYSICAL REQUIREMENTS

• 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
• Hearing and speech to communicate

*This is a direct hire. Please, no outside Agency solicitations.

Apptronik provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Technology Control Restrictions: As a person in this position will have access to technical data and/or computer software maintained by the Company, which includes export‑controlled technical data and/or computer software, successful applicants must be eligible under U.S. export control regulations to access such information.