2027 Summer Intern, PhD, Machine Learning - Simulation & Closed-Loop Training

Waymo, Mountain View, California +1

What you will do

Design, implement, and scale Reinforcement Learning post-training and distillation algorithms (such as flow or diffusion policy optimization, off-policy importance sampling, and constrained multi-objective RL) for foundation world models in simulation and autonomous driving
Develop learned reward models, realism critics, and discriminators within a closed-loop multi-agent simulator to align simulated agent and driving behaviors with human driving realism and safety
Run rigorous closed-loop ablation studies on large-scale TPU clusters—leveraging agentic auto-research workflows and fleet-scale driving behavior metrics (such as route progress, braking comfort, lateral stability, and lane selection)—to mitigate simulator exploitation and distribution shift

All jobs

2027 Summer Intern, PhD, Machine Learning - Simulation & Closed-Loop Training

Waymo, Mountain View, California +1

What you will do

Design, implement, and scale Reinforcement Learning post-training and distillation algorithms (such as flow or diffusion policy optimization, off-policy importance sampling, and constrained multi-objective RL) for foundation world models in simulation and autonomous driving
Develop learned reward models, realism critics, and discriminators within a closed-loop multi-agent simulator to align simulated agent and driving behaviors with human driving realism and safety
Run rigorous closed-loop ablation studies on large-scale TPU clusters—leveraging agentic auto-research workflows and fleet-scale driving behavior metrics (such as route progress, braking comfort, lateral stability, and lane selection)—to mitigate simulator exploitation and distribution shift

What you need

Currently pursuing a PhD in Computer Science, Machine Learning, Robotics, or a related technical field, with an anticipated graduation date between December 2027 and August 2028 (returning to a degree program for at least one academic term after the internship)
Core Implementation Fluency (Mandatory): Strong tensor implementation and debugging skills in Python and JAX/Flax or PyTorch, with hands-on experience training and modifying modern neural architectures (such as Transformers, Diffusion/Flow models, or deep RL networks)
Deep Research Expertise in Either (a) Reinforcement Learning & Post-Training (hands-on research experience in policy gradient methods such as PPO/GRPO/REINFORCE, off-policy or offline RL such as importance sampling/AWR/DPO, constrained MDPs, inverse RL, or learned reward and critic modeling) OR (b) Generative World, Sequence, or Trajectory Modeling (hands-on research experience in continuous flow matching / Rectified Flows, score-based diffusion policies such as DDPO/DPPO/Diffuser, or spatiotemporal autoregressive world and trajectory models), with working familiarity in the other

We prefer

First-author publications at top-tier machine learning or robotics venues (e.g., NeurIPS, ICML, ICLR, CVPR, CoRL, RSS, ICRA, or equivalent venues) in RL post-training, flow/diffusion policy optimization, generative world models, or autonomous driving
Experience with multi-agent closed-loop simulation, Sim2Real transfer, or reward-hacking mitigation (e.g., Waymax, WOMD, NuPlan, IsaacGym/MuJoCo, adversarial traffic generation, or discriminator stabilization)
Experience profiling and scaling distributed training workloads on TPUs or multi-node GPUs (such as XLA compilation, vectorized batched rollouts, and memory optimization) and familiarity with C++/Python interfaces

Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in.

The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements.

2027 Summer Intern, PhD, Machine Learning - Simulation & Closed-Loop Training

What you will do

2027 Summer Intern, PhD, Machine Learning - Simulation & Closed-Loop Training

What you will do

What you need

We prefer

Hourly PhD Pay

About Waymo

Similar jobs at other companies

PhD Machine Learning Software Engineer Intern (Summer 2027)

Reinforcement Learning and World Model for Autonomous Simulation Intern - 2027

Applied Scientist Intern, PhD (Summer 2027)

Reinforcement Learning Intern - 2027

Applied Scientist/Machine Learning Engineer, Gaia

Applied Deep Learning Algorithm Intern, Autonomous Driving - 2027

Waymo