Staff Tech Lead Manager (Machine Learning, Simulator Evaluation)

Join Waymo, a leader in autonomous driving technology. As a Staff Tech Lead Manager, you will lead a top-tier applied ML team focused on building evaluation frameworks, infrastructure, and AI-powered tooling for World Model understanding and evaluation. You will drive technical direction, architect ML-driven metrics, and partner with cross-functional teams to deploy your team's solutions into Waymo's production-critical systems. Enjoy a comprehensive benefits package, including medical, dental, and vision insurance, competitive compensation, and a hybrid work model.

• Lead a top-tier applied ML team focused on building evaluation frameworks, infrastructure, and AI-powered tooling for World Model understanding and evaluation.
• Drive technical direction, and provide technical inputs and guidance to the team, architecting ML-driven metrics and evaluation frameworks.
• Partner with cross-functional teams and senior technical leadership to deploy your team’s solutions into Waymo’s production-critical systems.

• 3+ years of hands-on technical leadership experience, directly managing and guiding high-performing engineering teams of 5-10 people
• Strong software engineering proficiency in Python and/or C++
• Proven ability to design robust evaluation frameworks for complex systems, combined with strong analytical skills and proficiency in large-scale data processing
• Experience with ML frameworks like PyTorch, JAX, or Tensorflow, backed by a solid foundation in deep learning, transformers, and large-scale model deployment
• Degree in Computer Science, Robotics, Machine Learning, a related technical field, or equivalent practical experience
• 7+ years of experience building, deploying, and optimizing machine learning systems in production environments
• 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