Waymo

Waymo

Posted via Greenhouse

Senior/Staff ML Engineer, 3D/4D World Modeling, Simulation

Posted Aug 5, 2026

Role at a glance

Salary
$213K – $263K/yr
Location
Mountain View, California, United States
Work arrangement
Hybrid
Employment
Full-time
Experience
5+ years of experience in ML engineering and applied Deep Learning
Education
MS or PhD in Computer Science, Machine Learning, Robotics, or a related field

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Role Summary

AI-generated

The Simulator Team develops realistic simulations for testing, training, and validation of the Waymo Driver, including dynamic agents, roads, traffic systems, weather, sensors, and semantic environments. This role leads 4D world modeling and generative systems that support scalable, controllable sensor and semantic generation for simulation.

What You'll Do

  • Lead the design, development and deployment of 4D world models and generative systems for sensor and semantics generation.
  • Architect and implement scalable ML pipelines for training, evaluating, and deploying large-scale generative models.
  • Build and scale production-ready video generation techniques, including Diffusion and Flow Matching.
  • Apply Vision Language Models to enhance semantic understanding and controllability of world simulation products.
  • Partner with research teams across Waymo and Alphabet to develop production-ready solutions.
  • Mentor and provide technical guidance to other engineers on the team.

Generated from the employer's posting. Verify important details before applying.

View full posting

Qualifications

MS or PhD in Computer Science, Machine Learning, Robotics, or a related field; 5+ years of experience in ML engineering and applied Deep Learning; experience developing and training large-scale generative models for video generation or Vision Language Models; expertise in 3D World Modeling or 3D computer vision; familiarity with 3D reconstruction and rendering techniques; strong Python programming skills and experience with Jax/Flax, PyTorch or Tensorflow.

Required

  • MS or PhD in Computer Science, Machine Learning, Robotics, or a related field
  • 5+ years of experience in ML engineering and applied Deep Learning
  • Proven experience in developing and training large-scale generative models for video generation or Vision Language Models
  • Deep expertise in 3D World Modeling or 3D computer vision
  • Familiarity with 3D reconstruction and rendering techniques
  • Strong programming skills in Python
  • Experience with ML frameworks such as Jax/Flax, PyTorch or Tensorflow

Preferred

  • PhD and a strong track record of delivering impactful ML products in 3D generative models, world models, or video generation
  • Experience in simulating sensor data (Camera, Lidar, Radar) and/or semantic scenes
  • Experience with autonomous systems, robotics, or autonomous vehicle simulation
  • Experience in training and optimizing large scale models on GPU/TPU clusters for efficient serving
  • Experience in C++ for production systems

Original job description

Content provided by the employer

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing, training, and validation of the Waymo Driver. Our team is a diverse, and collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers. We develop industry-leading simulation solutions using advanced generative and reconstructive ML algorithms, to model the real world, encompassing realistic agents, roads, traffic systems, weather, and the full sensor suite (Camera, Lidar, Radar).

To accelerate the fidelity, scalability, controllability, and richness of our simulations, we are pushing the frontiers of 3D world modeling. We leverage state-of-the-art ML technologies trained on large-scale datasets to create dynamic and semantically rich virtual worlds, directly impacting the development and validation of the Waymo Driver.

In this role, you will report to a Senior Staff Engineering Manager.

 

You will:

  • Lead the design, development and deployment of cutting-edge 4D world models and generative systems for ultra-realistic and controllable sensor and semantics generation for simulation use cases at waymo.
  • Architect and implement scalable and robust ML pipelines for training, evaluating, and deploying large-scale generative models into our simulation infrastructure, including techniques like model distillation and quantization.
  • Build and scale production-ready video generation techniques (e.g., Diffusion, Flow Matching) to create dynamic and interactive simulation environments.
  • Apply Vision Language Models (VLMs) to enhance the semantic understanding and controllability of our world simulation products.
  • Partner with world class research teams across Waymo and Alphabet to leverage State-of-The-Art research in 4D world modeling and generative AI into robust, production-ready solutions.
  • Mentor and provide technical guidance to other engineers on the team.

 

You have:

  • MS or PhD in Computer Science, Machine Learning, Robotics, or a related field.
  • 5+ years of experience in ML engineering and applied Deep Learning, with a strong portfolio of shipped products or publication record.
  • Proven experience in developing and training large-scale generative models for video generation (e.g., Diffusion models, Flow Matching) or Vision Language Models (VLMs) and their applications.
  • Deep expertise in 3D World Modeling or 3D computer vision.
  • Familiarity with 3D reconstruction and rendering techniques (e.g., 3D Gaussian Splatting).
  • Strong programming skills in Python and experience with ML frameworks such as Jax/Flax, PyTorch or Tensorflow.

 

We prefer:

  • PhD and a strong track record of delivering impactful ML products in 3D generative models, world models, or video generation..
  • Experience in simulating sensor data (Camera, Lidar, Radar) and/or semantic scenes.
  • Experience with autonomous systems, robotics, or autonomous vehicle simulation.
  • Experience in training and optimizing large scale models on GPU/TPU clusters for efficient serving.
  • Experience in C++ for production systems.

 

#LI-Hybrid

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. 

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. 

Salary Range
$213,000$263,000 USD
Waymo

About the company

Waymo

Large Enterprise

Waymo is a leading autonomous driving technology company, originally a part of Google's parent company Alphabet Inc. Established in 2009, Waymo focuses on developing self-driving cars and innovative transportation solutions designed to enhance mobility and safety on the roads. By employing advanced artificial intelligence and machine learning algorithms, the company aims to revolutionize personal and shared transportation, making it more accessible and efficient. Waymo's efforts contribute significantly to the future of autonomous vehicles and the ongoing shift towards smart transportation systems.