Group Product Manager, ML Infrastructure

About the position

Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states. Waymo’s Product Management Team is a mission-driven team responsible for writing and enacting first-of-their-kind playbooks to bring fully autonomous driving technology to market. Our team develops simple solutions for complex problems by orchestrating cross-functional efforts to safely drive Waymo’s technology and the products it enables forward. We do this by understanding the customer, the business, and the technology.

Responsibilities

• Define and maintain the multi-year product vision, strategy, and roadmap for Waymo's internal ML Infrastructure platform, encompassing data management, large-scale distributed training, rigorous evaluation, efficient deployment, and advanced MLOps capabilities
• Deeply understand the needs and workflows of Waymo's internal ML practitioners (engineers, researchers) through continuous engagement and collaboration, translating these needs into actionable platform improvements
• Partner closely with Engineering, Research, and other stakeholders to ensure alignment on platform priorities, define clear requirements, and drive the successful development and adoption of new capabilities
• Oversee the end-to-end product lifecycle, prioritizing initiatives that maximize ML developer velocity, model performance, system scalability, and efficient resource utilization
• Actively participate in technical discussions, offering guidance on ML frameworks, distributed systems design, hardware acceleration strategies, and MLOps best practices

Requirements

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience
• 10+ years of combined experience in product management, technical program management, software engineering, or machine learning engineering
• 5+ years of direct experience building, launching, and iterating on technical platforms, cloud infrastructure, developer tools, or large-scale machine learning systems
• Demonstrated experience leading complex, technical projects with cross-functional teams from initial concept through successful delivery and adoption
• A strong understanding of the machine learning development lifecycle (data preparation, training, evaluation, deployment, monitoring)
• Familiarity with common ML frameworks (e.g., TensorFlow, PyTorch, JAX) and foundational infrastructure concepts including compute, storage, networking, and distributed systems

Nice-to-haves

• Experience building internal developer platforms, tools, or infrastructure within a large, complex engineering organization
• Hands-on experience with technologies and challenges related to large-scale distributed training, MLOps implementation, ML model optimization, and leveraging hardware accelerators (GPUs, TPUs) effectively
• Proven ability to influence and align senior leadership (Director, VP level) and drive strategic initiatives in a dynamic, fast-paced, and technically demanding environment

Benefits

• Discretionary annual bonus program
• Equity incentive plan
• Generous Company benefits program