RL Robotics Research Intern: Locomotion & Planning

FieldAI; Irvine (CA); On-site; USD 54,000 - 67,000; Full time

Benefits offered by this job

Onsite Irvine

Research internship

Hardware access

Job summary

Field AI invites PhD students to join a Summer 2026 internship focused on learning-based locomotion and planning for autonomous legged robots. You will work at the intersection of reinforcement learning, locomotion control, and learned planning to build integrated systems for real-world robotics.

You will collaborate with Field AI researchers to design experiments, validate ideas in simulation and on hardware, and help translate research into deployable capabilities for field deployment.

Qualifications

• Current PhD student in Robotics, CS, Mechanical Engineering, AI/ML or related field.
• Research experience in reinforcement learning for continuous control or planning.
• Strong foundation in locomotion, control theory, and kinematics.

Responsibilities

• Design, implement, and evaluate RL pipelines that integrate locomotion with planning.
• Explore learned planners to adapt locomotion across varied terrain and conditions.
• Conduct simulation experiments and on-robot validation with real hardware.

Skills

Reinforcement learning

Locomotion control

Learned planning

Python

C++

Education

PhD student in Robotics/CS/ME/AI

Tools

Isaac Gym

MuJoCo

PyBullet

ROS2

Job description

Field AI invites PhD students to join a Summer 2026 internship focused on learning-based locomotion and planning for autonomous legged robots. You will work at the intersection of reinforcement learning, locomotion control, and learned planning to build integrated systems for real-world robotics.

You will collaborate with Field AI researchers to design experiments, validate ideas in simulation and on hardware, and help translate research into deployable capabilities for field deployment.