Robotics Engineering Intern

Intuitive•Sunnyvale, CA

3h•$62 - $82•Onsite

About The Position

The Robotics Engineering Intern will report to the future forward research lab and contribute to creating a sim-to-real-to-sim platform for Intuitive’s surgical robot system. The role supports rapid prototyping and de-risking of new controller architectures, particularly data-hungry semi-supervised and supervised autonomous systems that require extensive validation. The intern will develop tools for transferring and testing controllers between simulation and robot hardware, build virtual models of the surgical field for simulation, and close the loop between simulation and reality to accelerate autonomous-controller development and evaluation.

Requirements

Must be currently enrolled in and returning to an accredited degree-seeking academic program after the internship.
Must be available to work full-time, approximately 40 hours per week, for a 10–12 week period starting in May or June.
Currently enrolled in a Robotics, Electrical Engineering, Mechanical Engineering, Computer Science, or related degree-seeking program at the Master's or Doctorate level.

Nice To Haves

Experience with MATLAB and/or Python for control system design and analysis.
Experience with MuJoCo or similar constrained rigid-body dynamics simulators.
Experience with sim-to-real transfer methods for robotic systems.
Familiarity with NVIDIA Isaac Sim or similar platforms for realistic rendering and simulation.
Familiarity with embedded C++ for low-level controller implementation.
Awareness of video-based 3D reconstruction and environment synthesis techniques.
Awareness of autonomous or semi-autonomous control architectures.

Responsibilities

Implement novel control architectures in high-level targets such as MATLAB and low-level targets such as embedded C++.
Systematically test controller performance in simulation and on robot hardware.
Create simulation environments integrating constrained rigid-body dynamics, such as MuJoCo, and realistic texture and lighting, such as Isaac Sim.
Synthesize simulated environments from video data, including geometry, texture, and inferred stiffness.
Conduct closed-loop round-trip tests by training controllers in simulation, testing them experimentally, and using experimental data to construct new simulation environments.