Robotics Simulation & Controls Intern – Robotics Simulation & Controls

Job Description

Robotics Simulation & Controls Intern | Eugenus, Inc.

The Tone:
This is an internship at Eugenus, Inc., located in San Jose, CA. Eugenus is undertaking an early-stage robotics R&D effort, focusing on simulation, control development, and sim-to-real transfer for legged robotic systems. This role is crucial for helping to establish a practical NVIDIA Isaac Sim / Isaac Lab workflow. The intern’s contributions will directly support robot modeling, reinforcement-learning experiments, actuator/sensor approximation, and the eventual transfer of learned behaviors from simulation to physical hardware.

The TL;DR
• Role: Internship
• Type: part time (up to 30 hours per week) temporary
• Location: In-person, San Jose, CA
• Pay: $25–$45 hourly
• Mission: This intern will help build a practical NVIDIA Isaac Sim / Isaac Lab workflow to support early-stage legged robotics R&D and eventual transfer from simulation to physical hardware.
• Tech Stack: Isaac Sim, Isaac Lab, Omniverse, Gazebo, MuJoCo, ROS 2, Python, C/C++, URDF, USD, PyTorch, Raspberry Pi, embedded Linux, serial communication, I2C, IMUs, servo motors, motor controllers, CAD (SolidWorks, Siemens NX, Fusion 360, Onshape), ChatGPT Business, Microsoft Copilot Premium, Github Copilot

What You’ll Actually Do
• Set up and document the NVIDIA Isaac Sim / Isaac Lab development environment, ensuring reproducibility.
• Build or adapt robot simulation assets, defining properties such as joints, collision geometry, mass/inertia, and sensor placements.
• Support the creation of simplified legged robot models for initial simulation and control testing.
• Develop basic reinforcement-learning or control experiments for behaviors like flat-terrain standing, balancing, or walking.
• Assist with the design of observation/action spaces, reward functions, termination conditions, domain randomization, and evaluation criteria for sim-to-real transfer.

The Must-Haves
• Background: Current B.S./M.S. student, recent graduate, or strong project-based candidate in Robotics, Mechatronics, Mechanical Engineering, Computer Engineering, Electrical Engineering, Computer Science, or related fields.
• Experience: Coursework or projects involving robotics, controls, dynamics, simulation, machine learning, reinforcement learning, autonomous systems, or mechatronics. Familiarity with at least one robotics simulation tool (Isaac Sim, Isaac Lab, Omniverse, Gazebo, MuJoCo) and one robotics/software tool (ROS 2, URDF, or USD).
• Skills: Python programming experience, comfort reading documentation, testing examples, debugging errors, and turning technical goals into working prototypes, strong written documentation habits.
• Bonus: Experience with legged robots or other autonomous robotics projects, exposure to advanced control methods like reinforcement learning or model-predictive control, understanding of rigid-body dynamics concepts, experience with embedded systems or physical robot prototyping, CAD exposure, or experience using AI tools (ChatGPT, Copilot) as part of an engineering workflow.