Staff Machine Learning Engineer (Infra) (AI)

TL;DR

Staff Machine Learning Engineer (Infra) (AI): Building and operating scalable ML and data systems for driver understanding and evaluation with an accent on large-scale model architectures and distributed training. Focus on designing planet-scale dataset generation, optimizing ML lifecycles, and implementing state-of-the-art autoregressive transformers.

Location: On Site in Mountain View, California

Salary: $238,000—$302,000 USD

Company

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver.

What you will do

• Provide deep technical leadership on large-scale ML model architectures for autonomous vehicles.
• Build scalable systems for training and fine-tuning large-scale models to evaluate driving behaviors.
• Design and scale distributed systems covering the ML lifecycle and planet-scale dataset generation.
• Oversee the production and optimization of ML models to assess a fleet of vehicles traveling millions of miles.
• Collaborate cross-functionally to derive performance and system-level requirements for large ML systems.
• Drive architectural decisions and technical directions to meet business objectives.

Requirements

• M.S. or Ph.D. degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
• 7+ years of professional software engineering experience.
• 3+ years in machine learning infrastructure (developing, designing, scaling, and optimizing).
• Strong history of contributions to ML tooling and frameworks (e.g., PyTorch, Jax, Tensorflow, Ray).
• Expertise in distributed training techniques, gradient sharding, and scaling models across accelerators.
• Deep understanding of state-of-the-art autoregressive transformers.

Nice to have

• 10+ years of SWE experience with 5+ years in ML infrastructure.
• Experience in the autonomous vehicles domain, robotics, or complex simulation environments.
• Deep understanding of RL techniques, including RLHF (human feedback/preferences).
• Familiarity with large-scale simulation platforms and ML training workflow integration.
• Track record of influencing senior stakeholders and driving innovation across team boundaries.

Culture & Benefits

• Participation in a discretionary annual bonus program.
• Equity incentive plan.
• Generous company benefits program.