Machine Learning Engineer (Infra), Driver Understanding and Evaluation

Job Summary

The DUE Machine Learning team at Waymo is seeking researchers and software engineers to develop and operate scalable machine learning and data systems, simulation workflow and insight tools, and improve and speed up the evaluation and onboard developer journeys. This role involves combining expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo driver.

About the Role

As a member of the DUE Machine Learning team, you will build and operate scalable systems for training and fine-tuning large-scale models to evaluate interesting driving behaviors. You will work at the intersection of data engineering, model development, and simulation, providing guidance on architectural decisions and technical directions. You will own large, complex systems, driving architectures that meet technical and business objectives. You will contribute to the production and optimization of machine learning models, design and scale large distributed systems covering the ML lifecycle, and collaborate cross-functionally to derive performance and system-level requirements for large ML systems. You will translate product/business goals into measurable technical deliverables, ensuring system component alignment.

Responsibilities

• Build scalable systems for training and fine-tuning large-scale models to evaluate interesting driving behaviors.
• Provide guidance on architectural decisions and technical directions.
• Own large, complex systems, driving architectures that meet technical and business objectives.
• Contribute to the production and optimization of machine learning models aiming to assess Waymo’s expansive fleet of vehicles that cumulatively travel millions of miles.
• Design and scale large distributed systems covering the ML lifecycle, supporting planet-scale dataset generation, model training, and evaluation.
• Collaborate cross-functionally to derive performance and system-level requirements for large ML systems.
• Translate product/business goals into measurable technical deliverables, ensuring system component alignment.

Requirements

• M.S. or Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience.
• 3+ years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model.
• A history of contributions to machine learning tooling and frameworks, e.g., PyTorch, Jax, Tensorflow, Ray, or similar.
• Strong expertise in distributed training techniques, including gradient sharding and optimization strategies for scaling large models across ML accelerator profiling tools to uncover performance bottlenecks.

Preferred

• 5+ years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model.
• Experience in the autonomous vehicles domain, robotics, or complex simulation environments.
• Familiarity with large-scale simulation platforms and their integration with ML training workflows.

Qualifications

• Passionate about developing machine learning techniques for the Evaluation systems on our autonomous vehicles.
• An incessant drive to improve the performance of our technology stack.

Skills

• Strong expertise in distributed training techniques, including gradient sharding and optimization strategies for scaling large models across ML accelerator profiling tools to uncover performance bottlenecks.

Benefits

Waymo offers a comprehensive benefits package including a discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. The expected base salary range for this full-time position across US locations is $170,000—$216,000 USD.