Waymo
Software Engineer
Mountain View, CA, USAFrom $310kfull-timemidAdded today
About this role
Waymo's AI Foundations team seeks a software engineer to integrate large-scale foundation models into autonomous driving production systems. You'll adapt models across new sensors and platforms while collaborating with cross-functional teams to deploy next-generation capabilities for the Waymo Driver.
What you'll do
- Connect large-scale foundation models with production autonomous driving systems
- Adapt foundation models to support new sensors, vehicle platforms, and production requirements
- Collaborate with multiple teams to integrate and land foundation models on next-generation platforms
- Solve complex system-level problems in large-scale deployments
- Work on LLM/VLM integration and deployment pipelines
- Support safe autonomous operation across diverse driving conditions and environments
What they're looking for
- Large-scale systems design and architecture
- Foundation models (LLM/VLM) experience
- Machine learning systems integration
- Cross-team collaboration and communication
- Production deployment and optimization
- Complex problem-solving
- Python or C++ programming
- Autonomous systems knowledge
Benefits
- Discretionary annual bonus program
- Equity incentive plan
- Generous company benefits package
- Work on cutting-edge autonomous driving technology
- Collaborate with top AI researchers
- Mountain View, CA location with potential remote flexibility
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 and deploying large-scale machine learning systems in production environments.
- Walk us through a complex system problem you solved involving foundation models or deep learning systems.