AI Robotics Researcher Intern (Dexterous Manipulation)
Core
Researching dexterous manipulation for robots using large-scale foundation models and human data-based learning to enable physical world intelligence.
Role type
AI Robotics Research Intern (Dexterous Manipulation)
Builds
Robust pipelines for converting human multi-modal data into actionable robot motor skills and sim-to-real validation of dexterous manipulation policies.
Domain
Embodied AI, Dexterous Manipulation, Human-Robot Interaction
Deliverable
production ML models | research
Required skills
Robot learning and control, Reinforcement learning, Imitation learning, Generative models, Transformer architectures, Robotic manipulation systems, Python, PyTorch, JAX, TensorFlow, ROS/ROS2, MuJoCo, Isaac Sim, PyBullet
Preferred skills
Dexterous manipulation, Multi-finger robotic hands, Sim-to-real transfer, Contact modeling, Tactile sensing, 3D perception, Reinforcement learning in continuous control, Top-tier conference publications
Technologies
PyTorch, JAX, TensorFlow, ROS, ROS2, MuJoCo, Isaac Sim, PyBullet
Responsibilities
Develop frameworks for transferring human-object interaction skills to robots, Architect autonomous pipelines for processing visual and human glove-collected data, Implement generative architectures for synthesizing robot trajectories, Explore cross-embodiment representations for unified policy training, Research sim-to-real deployment techniques, Utilize vision-language models for semantic scene understanding
Seniority
Intern, research execution
