Robotics Research Intern: RL Locomotion & Planning

Field Ai; Irvine (CA); On-site; USD 62,000 - 83,000; Full time

Job summary

Field AI invites a Summer 2026 research internship for PhD students to advance learning-based locomotion and planning for real-world legged robots. You'll collaborate with our research scientists to design experiments, develop integrated locomotion and planning systems, and validate ideas in simulation and on hardware.

Responsibilities include designing RL-based pipelines, bridging sim-to-real gaps, and building tooling that connects research to deployment.

Qualifications

• Current PhD student in Robotics, Computer Science, Mechanical Engineering, AI/ML, or closely related field.
• Research experience in reinforcement learning for locomotion or planning.
• Strong foundation in contact dynamics, control theory, and kinematics.
• Proficiency in Python and/or C++, with robotics or ML tooling experience.

Responsibilities

• Advance RL-based locomotion and learned planning research and experiments.
• Bridge locomotion and planning across the sim-to-real gap with domain randomization and testing.
• Build systems that connect research concepts to deployment on real hardware.
• Collaborate with systems engineers, perception experts, and embedded teams.
• Prototype rapidly, run sims and on-robot experiments, analyze results.

Skills

Python

C++

RL tooling

Robotics experience

Education

PhD student in Robotics/CS/ME/AI

Tools

Isaac Gym

MuJoCo

PyBullet

ROS/ROS2

Job description

Field AI invites a Summer 2026 research internship for PhD students to advance learning-based locomotion and planning for real-world legged robots. You'll collaborate with our research scientists to design experiments, develop integrated locomotion and planning systems, and validate ideas in simulation and on hardware.

Responsibilities include designing RL-based pipelines, bridging sim-to-real gaps, and building tooling that connects research to deployment.