Robotics Intern (Part Time)

Faraday Future•El Segundo, CA

8d•$32 - $41

About The Position

We are looking for a highly motivated Robotics Intern (Part Time) to support robotics control and learning projects. This role is ideal for graduate students who want hands-on experience in robot locomotion, reinforcement learning, simulation, and experimental validation while working closely with a motion control team building real robotic systems.

Requirements

Currently pursuing a Master’s or PhD degree in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, Artificial Intelligence, or a related field.
Strong Python programming skills, including experience developing and debugging technical or research-oriented code.
Strong foundation in applied mathematics, including areas such as linear algebra, calculus, probability, optimization, or control theory.
Hands-on experience or academic research in one or more of the following domains: robotics, reinforcement learning, motion planning and control, optimization, or physics-based simulation.
Familiarity with robotics development and experimentation workflows, including iterative testing, evaluation, and debugging.
Strong problem-solving ability and willingness to debug experiments independently.
Demonstrated analytical and problem-solving skills, with the ability to independently troubleshoot technical challenges and debug experimental results.

Nice To Haves

Hands-on experience with PyTorch, reinforcement learning libraries, or imitation learning workflows.
Familiarity with MuJoCo, Isaac Gym, Isaac Lab, Gazebo, or other robotics simulation environments.
Hands-on experience with quadruped robots, humanoids, or legged robot simulation/training environments is highly preferred.
Experience with reinforcement learning training pipelines, policy optimization, or sim-to-real workflows.
Prior robotics project, lab, or competition experience is strongly preferred.
Basic C++ knowledge is a plus.
Ability to document experiments clearly and communicate insights effectively.

Responsibilities

Support locomotion, motion control, or learning-based robotics projects in simulation and on hardware when appropriate.
Implement and run reinforcement learning, imitation learning, or control experiments under guidance from the team.
Build tools for logging, visualization, replay, benchmarking, and experiment analysis.
Assist with simulator setup, training pipelines, evaluation scripts, and result reporting.
Help collect, organize, and analyze robot experiment data for controller tuning and performance debugging.
Contribute to prototype features, research explorations, and internal demos related to motion control and robotics learning.