2 days ago
Responsibilities
- Implement and tune control algorithms for multi-fingered hands, including grasping, in-hand manipulation, and tactile-feedback integration.
- Develop and maintain low-latency manipulation software within the real-time controls stack.
- Translate reinforcement-learning, imitation-learning, and human-to-robot motion-retargeting methods into production-grade C++ and Python.
- Build and refine sim-to-real pipelines using hand models, domain randomization, and physics simulation.
- Deploy and debug manipulation capabilities on physical robots, diagnosing sensor noise, latency, and calibration issues.
- Collaborate with hardware and systems engineers on hand performance and sensor and actuator requirements.
- Maintain code quality through testing, documentation, and peer review.
Requirements
- Experience with dexterous manipulation, including multi-fingered grasping, in-hand manipulation, and high-DOF hand control.
- Experience applying reinforcement learning to robotic control, including reward design, training, and debugging; imitation learning and diffusion policies are a plus.
- Strong Python and working C++ skills for real-time robotic software.
- Hands-on experience training and validating policies in IsaacSim, MuJoCo, or Drake.
- Knowledge of robotics fundamentals including kinematics, dynamics, and Jacobian-based control.
- Track record of deploying complex algorithms on physical hardware rather than simulation alone.
- Bachelor’s, master’s, or PhD degree in Robotics, Computer Science, Electrical Engineering, or a related field.
- At least 3 years of relevant experience in robotic manipulation or complex motion control; recent PhD graduates are considered.
- Preferred experience includes VR or haptic teleoperation and retargeting, tactile-sensing integration, computer vision involving 6D pose or point clouds, and end-effector bring-up and calibration.
Benefits
- Direct-hire position.
- Equal employment opportunity and anti-discrimination protections are provided.
About Apptronik
Apptronik designs and manufactures AI-enabled humanoid robots, led by its Apollo platform, to automate tasks alongside people in manufacturing and logistics, with potential use in healthcare and homes. The privately held company is headquartered in Austin, Texas, and grew out of the University of Texas at Austin’s Human Centered Robotics Lab; its team previously worked on NASA’s Valkyrie robot. Apptronik’s business model centers on selling robots and the software and services needed to deploy them in industrial environments.