Senior ML Engineer - Simulation & World Modeling

Waymo LLC; Mountain View (CA); Hybrid; USD 213,000 - 263,000; Full time

Benefits offered by this job

Annual bonus

Equity incentives

Benefits program

Job summary

Waymo LLC's Simulator Team seeks a seasoned ML Engineer to advance ultra-realistic world simulation for autonomous vehicles. You will design and scale foundation models for embodied agents and collaborate with research to productionize scalable solutions.

You will own end-to-end ML pipelines including multimodal world models, training loops, and reinforcement learning workflows, leveraging PyTorch/TensorFlow/JAX.

Qualifications

• 5+ years of experience with ML software engineering.
• 5+ years of Python experience.
• 5+ years of ML software experience with machine learning frameworks including PyTorch, TensorFlow, or JAX/Flax.
• Demonstrated experience building, training, or scaling world models or multi-modal models on large-scale datasets (e.g., video, images, text)
• Hands-on experience with closed-loop training, policy learning, or reinforcement learning frameworks
• Prefer robotics, control theory, or embodied AI experience; production-ready ML integration in autonomous driving would be a plus
• Experience in training large-scale models on GPU/TPU clusters

Responsibilities

• Drive innovation in ultra-realistic world simulation for autonomous vehicles by developing and scaling foundation models for embodied agents.
• Design and train multimodal world models and generative architectures using diverse sensory data.
• Drive closed-loop training and reinforcement learning pipelines to advance simulation realism, policy optimization, and decision-making for autonomous driving.
• Work with Waymo's foundational AI research team to transfer research into scalable, production-ready solutions

Skills

ML software engineering

Python

PyTorch

TensorFlow

JAX/Flax

World models

Multimodal models

Reinforcement learning

Tools

C++

Job description

Waymo LLC's Simulator Team seeks a seasoned ML Engineer to advance ultra-realistic world simulation for autonomous vehicles. You will design and scale foundation models for embodied agents and collaborate with research to productionize scalable solutions.

You will own end-to-end ML pipelines including multimodal world models, training loops, and reinforcement learning workflows, leveraging PyTorch/TensorFlow/JAX.