Robotics Intern (Part Time)

The Company: Faraday Future (FF) is a California-based embodied artificial intelligence ecosystem company, leveraging the latest technologies and world’s best talent to realize exciting new possibilities in mobility and robotics. We’re producing user-centric, technology-first vehicles and robots to establish new paradigms in human‑AI interaction. We’re not just seeking to change how our cars and robots work – we’re seeking to change the way we drive and interact with machines. At FF, we’re creating something new, something connected, and something with a true global impact. Your Role: 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. 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. Basic Qualifications: 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. Preferred Qualifications: 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. Hourly Salary Range: (\$28/hr - \$41/hr DOE), plus benefits and incentive plans Perks + Benefits Healthcare + dental + vision benefits (Free for you/discounted for family) 401(k) options Casual dress code + relaxed work environment Culturally diverse, progressive atmosphere Faraday Future is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. #J-18808-Ljbffr Faradayfuture