PhD ML Intern: Simulation & Closed-Loop RL

First Roles; Mountain View (CA); Hybrid; USD 97,000 - 138,000; Full time

Benefits offered by this job

Benefits programs

Job summary

Waymo is hiring a PhD intern to advance reinforcement learning post-training and closed-loop simulation for autonomous driving. You will work on cutting-edge world models, diffusion policy optimization, and multi-agent simulators to align simulated behavior with safe, human-like driving.

This hybrid onsite internship is based in Mountain View, CA, with a mix of in-person and remote work. Ideal candidates are pursuing a PhD with strong Python and JAX/PyTorch skills, and hands-on experience in RL,

Qualifications

• PhD in CS/ML/Robotics or closely related field.
• Strong programming and deep learning background required.
• Experience with RL, world models, or diffusion models is highly preferred.

Responsibilities

• Design, implement, and scale reinforcement learning post-training algorithms in simulation and closed-loop training.
• Develop learned reward models, realism critics, and discriminators in a multi-agent simulator.
• Collaborate with simulation, world modeling, and autonomous driving teams to validate and improve models.

Skills

Python

JAX/Flax

PyTorch

Tensor computation

Education

PhD in Computer Science / ML / Robotics

Tools

TPUs

GPUs

XLA

Job description

Waymo is hiring a PhD intern to advance reinforcement learning post-training and closed-loop simulation for autonomous driving. You will work on cutting-edge world models, diffusion policy optimization, and multi-agent simulators to align simulated behavior with safe, human-like driving.

This hybrid onsite internship is based in Mountain View, CA, with a mix of in-person and remote work. Ideal candidates are pursuing a PhD with strong Python and JAX/PyTorch skills, and hands-on experience in RL,