Waymo
ML Engineer, Foundation Model Infrastructure
About this role
Waymo seeks an ML Engineer to build and operate large-scale data systems and ML infrastructure supporting foundation model development for autonomous driving. You'll shepherd cutting-edge models from research to production, create automated benchmarking and deployment systems, and partner with AI researchers to drive on-road improvements.
What you'll do
- Build and operate petabyte-scale data systems and ML pipelines for foundation model development
- Transition foundation models from prototypes to robust production components in the Waymo Driver
- Create automated infrastructure for benchmarking, monitoring, and safely releasing models
- Process massive datasets and train/deploy complex models using large-scale compute and frameworks like Flume and JAX
- Improve speed, reliability, and efficiency of the end-to-end ML development lifecycle
- Collaborate with AI Foundations and ML Platform teams to translate innovations into on-road improvements
What they're looking for
- Python
- C++
- Deep learning frameworks (PyTorch, JAX, or TensorFlow)
- Large-scale data pipeline design (Flume, Spark, or similar)
- ML infrastructure and MLOps platforms
- Distributed systems architecture
- Software engineering for complex codebases
- ML model evaluation and benchmarking methodologies
Benefits
- Discretionary annual bonus program
- Equity incentive plan
- Generous company benefits program
- Hybrid work arrangement
- Work on autonomous driving technology impacting safety
- Collaboration with leading AI research teams
Opens the official application on the employer’s site. No login required.
Waymo
Waymo develops autonomous driving technology and vehicles, building the AI systems, simulation platforms, and infrastructure that power the Waymo Driver. The company is hiring for ML infrastructure engineers, platform engineers, labeling system developers, backend software engineers, and automotive systems engineers to scale its autonomous driving capabilities.
- Website
- waymo.com
Likely interview questions
- Describe your experience building or maintaining large-scale data pipelines—what frameworks did you use and what were the key challenges?
- How have you approached optimizing ML training pipelines for speed and efficiency at scale?