Senior Machine Learning Engineer (Infra), Driver Understanding and Evaluation

Job description

Job responsibilities

• Build scalable systems for training and fine-tuning large-scale models to evaluate interesting driving behaviors.
• Work at the intersection of data engineering, model development, and simulation Provide guidance on architectural decisions and technical directions.
• 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.

Job requirements

• M.S. or Ph.D. degree Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience.
• 5+ 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. The candidate should understand both the user facing API and the internal workings.
• 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.