Staff Tech Lead Manager (Machine Learning)

TL;DR

Staff Tech Lead Manager (Machine Learning): Leading an applied ML team to build evaluation frameworks and AI-powered tooling for World Model understanding with an accent on scaling technical vision and managing specialized engineering teams. Focus on architecting ML-driven metrics to rigorously test World Model quality and automating the detection of anomalies across vast datasets.

Location: On Site, Mountain View, California

Salary: $238,000—$302,000 USD

Company

Waymo is an autonomous driving technology company building the Waymo Driver to improve mobility and safety through fully autonomous ride-hailing services.

What you will do

• Lead a top-tier applied ML team focused on evaluation frameworks, infrastructure, and AI-powered tooling for World Model understanding.
• Architect ML-driven metrics and evaluation frameworks to rigorously test World Model quality and surface anomalies.
• Drive technical direction and translate complex modeling challenges into clear business objectives.
• Build internal AI-powered tools and products to streamline the model evaluation journey and iteration workflows.
• Partner with cross-functional teams and senior leadership to deploy solutions into production-critical systems.

Requirements

• Degree in Computer Science, Robotics, Machine Learning, or equivalent practical experience.
• 3+ years of hands-on technical leadership experience managing engineering teams of 5-10 people.
• 7+ years of experience building, deploying, and optimizing ML systems in production.
• Strong software engineering proficiency in Python and/or C++.
• Experience with ML frameworks like PyTorch, JAX, or TensorFlow, with a foundation in deep learning and transformers.
• Proven ability to design robust evaluation frameworks and handle large-scale data processing.

Nice to have

• M.S. or PhD in Computer Science, Robotics, Machine Learning, or a related quantitative field.
• Track record of training or evaluating large-scale generative models (RL, diffusion, world models, video generation).
• Experience optimizing models on massive GPU/TPU clusters and managing MLOps systems.
• Experience building AI-powered developer tools to automate complex workflows.

Culture & Benefits

• Discretionary annual bonus program and equity incentive plan.
• Generous comprehensive company benefits program.
• Opportunity to work with one of the most complex virtual environments ever built.
• Inclusive engineering culture characterized by extreme technical rigor and rapid experimentation.