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60 Waymo Machine Learning Scientist Jobs Hiring Near You

Waymo

Data Scientist

Mountain View, CA · On-site

$170K - $216K/yr

Experience in adjacent relevant areas like Advanced Machine Learning (Deep Learning and Diffusion ... Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program ...

Waymo

Senior Data Scientist

Mountain View, CA · On-site

$204K - $259K/yr

Experience in adjacent relevant areas like Advanced Machine Learning (Deep Learning and Diffusion ... Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program ...

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Waymo Jobs Information

What is it like to work at Waymo?

Waymo is a technology company that values innovation, collaboration, and safety, fostering an environment where employees can work together to develop and implement autonomous driving solutions.

The company's structure is organized into various teams, including software engineering, hardware development, and operations, allowing employees to specialize in their areas of expertise and contribute to the development of self-driving cars. Waymo's work environment is designed to encourage creativity and experimentation, with access to cutting-edge technology and resources.

Working at Waymo may appeal to individuals who are passionate about transforming the transportation industry and have a strong interest in artificial intelligence, machine learning, and software development, as the company offers opportunities to work on complex technical challenges and make a meaningful impact on society.

What makes Waymo an attractive place to work?

Waymo is a leading autonomous driving technology company, a subsidiary of Alphabet Inc., and a pioneer in the development of self-driving cars. The company's workplace is characterized by a culture of innovation, collaboration, and experimentation, with opportunities for engineers and researchers to work on cutting-edge projects and contribute to the advancement of autonomous driving technology. Joining Waymo offers the chance to be part of a team that is shaping the future of transportation and mobility, with opportunities for professional growth, learning, and making a meaningful impact on society.

What other companies are hiring for Machine Learning Scientist jobs?

What are the most popular jobs at Waymo?

What are the most popular categories at Waymo?

Infographic showing various Machine Learning Scientist job openings at Waymo in the United States as of September 2026, with employment types broken down into 1% Internship, and 99% Full Time. Highlights an 70% Physical, 27% Hybrid, and 3% Remote job distribution.

Staff Tech Lead Manager, Machine Learning, Simulator Evaluation

San Diego, CA • On-site

Waymo
Internet and IT • 1 - 5K employees
Learn more about Waymoexternal

Full-time

Re-posted 2 days ago

Key responsibilities

  • Lead a top-tier applied ML team focused on building evaluation frameworks, infrastructure, and AI-powered tooling for World Model understanding and evaluation.

  • Architect ML-driven metrics and evaluation frameworks that rigorously test World Model quality, automatically surfacing anomalies and edge cases across datasets.

  • Build AI-powered internal tools and products that streamline the model evaluation process for users, transforming complex model analysis into automated workflows.

Job description

About the Role

Waymo's simulator is one of the most complex virtual environments ever built, blending deterministic logic, physical dynamics, and state-of-the-art Generative AI to create a training ground for the Waymo Driver. Within this cutting-edge ecosystem, the Simulator Evaluation team faces the ultimate data challenge: How do you mathematically prove that a virtual world is "real"?

While our team programmatically builds the metrics, pipelines, and ML systems that grade this hybrid environment, your challenge as a Staff Tech Lead Manager is to scale both this technology and the highly specialized team executing this vision. In this role, you will bridge technical vision and execution by translating cutting-edge generative AI advancements into production-ready evaluation tools used by engineering teams across Waymo to ensure the safety and performance of our autonomous fleet, while fostering an inclusive engineering culture of extreme technical rigor, rapid experimentation, and robust software quality.

You will:
  • Lead a top-tier applied ML team focused on building eval frameworks, infrastructure, and AI-powered tooling for World Model understanding and evaluation.
  • Drive technical direction, and provide technical inputs and guidance to the team.
  • Architect ML-driven metrics and evaluation frameworks that rigorously test World Model quality, automatically surfacing anomalies and edge cases across vast datasets.
  • Chart the technical direction for World Model evaluation, working closely with Product and Program managers to translate modeling challenges into clear business objectives.
  • Build AI-powered internal tools and products that streamline the model eval journey for users, transforming complex model analysis into intuitive, automated, fast-iteration workflows.
  • Partner with cross-functional teams (e.g., Onboard, Research, and other Simulation teams) and senior technical leadership to deploy your team's solutions into Waymo's production-critical systems.
You have:
  • Degree in Computer Science, Robotics, Machine Learning, a related technical field, or equivalent practical experience
  • 3+ years of hands-on technical leadership experience, directly managing and guiding high-performing engineering teams of 5-10 people
  • 7+ years of experience building, deploying, and optimizing machine learning systems in production environments
  • Strong software engineering proficiency in Python and/or C++
  • Experience with ML frameworks like PyTorch, JAX, or Tensorflow, backed by a solid foundation in deep learning, transformers, and large-scale model deployment
  • Proven ability to design robust evaluation frameworks for complex systems, combined with strong analytical skills and proficiency in large-scale data processing
We Prefer:
  • M.S. or PhD. in Computer Science, Robotics, Machine Learning, or a related quantitative field.
  • A proven track record of training and/or evaluating large-scale generative models (e.g., reinforcement learning, diffusion, world models, 3D generative models, or video generation)
  • Experience training and optimizing models on massive GPU/TPU clusters, and managing large-scale data processing/MLOps systems
  • Experience building and deploying AI-powered products or internal developer tools that streamline or automate complex workflows

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