Dexterous Robot Manipulation Intern – On-Site Palo Alto

Realhand Inc.; Palo Alto (CA); Hybrid; USD 44.000 - 103.000; Teilzeit

Zusammenfassung

RealHand Inc. in Palo Alto, CA is seeking a Robot Manipulation & Control Intern to work on controlling dexterous hands and arms, building controllers, perception stacks, and learning-based policies for real hardware.

You will collaborate with ML teams, simulate with physics engines, and write production-quality Python/C++ code for robotic platforms. The internship focuses on translating policy into action with emphasis on real-world validation in simulation and on hardware, with a direct path to

Qualifikationen

• Experience deploying software on real robot hardware.
• Strong robotics fundamentals: kinematics, dynamics, control theory, motion planning, and contact mechanics.
• Experience with ROS/ROS2 and full robotics software stacks.
• Experience with physics simulators for contact-rich manipulation (Isaac Sim, MuJoCo, Genesis, SAPIEN, etc.).
• Familiarity with egocentric and wrist-mounted cameras; calibration challenges.
• Proficiency in Python and C++; experience with a DL framework.

Aufgaben

• Develop and tune controllers for dexterous hands and arms: impedance and admittance control, force and tactile feedback, compliant contact behavior, and in-hand manipulation primitives
• Implement manipulation behaviors including grasping, pick-and-place, object reorientation, tool use, and bimanual coordination — as classical pipelines, learned policies, or hybrids
• Build perception for manipulation: egocentric and eye-in-hand pose estimation, grasp affordance prediction, 6-DoF object pose, and visual servoing under occlusion by the hand itself
• Model the hand and its contact behavior in physical simulation, validate that simulated controller performance predicts real performance, and close the gap where it does not
• Write and maintain production-quality Python and C++ for robot platforms: real-time loops, hardware interfaces, safety limits, and tests
• Collaborate with the ML team to deploy learned policies on hardware — latency budgets, observation and action space design, safety envelopes, and failure fallback
• Build calibration, system identification, and diagnostic tooling so the platform stays trustworthy over months of use
• Evaluate tradeoffs between classical control and learning-based approaches and make principled design decisions
• Continuously improve robotic software for performance, reliability, and scalability

Kenntnisse

Robotics fundamentals

Python

C++

ROS/ROS2

Control theory

Experiment design

Simulation experience

Ausbildung

MS/PhD in Robotics or CS or related

Tools

Isaac Sim

MuJoCo

Genesis

SAPIEN

Robot hardware interfaces

Jobbeschreibung

RealHand Inc. in Palo Alto, CA is seeking a Robot Manipulation & Control Intern to work on controlling dexterous hands and arms, building controllers, perception stacks, and learning-based policies for real hardware.

You will collaborate with ML teams, simulate with physics engines, and write production-quality Python/C++ code for robotic platforms. The internship focuses on translating policy into action with emphasis on real-world validation in simulation and on hardware, with a direct path to