Waymo
2027 Summer Intern, MS/PhD, Software Engineer, Multiverse
Mountain View, California, USAinternshipinternAdded today
About this role
Waymo seeks MS/PhD software engineering interns to contribute to autonomous driving technology by analyzing vehicle behavior patterns, building automated detection pipelines, and developing performance metrics for the Waymo Driver platform.
What you'll do
- Conduct cluster analysis on autonomous vehicle driving behaviors
- Build tools and automated pipelines to detect and respond to undesirable driving events
- Design and validate signals to identify problematic driving behaviors
- Develop metrics to quantify and track Waymo's overall driving performance
- Experiment with improvements to behavior detection precision
- Collaborate on data-driven solutions for autonomous vehicle safety
What they're looking for
- Python or C++
- SQL or Python for data analysis
- Data fluency and statistical analysis
- Machine learning model training and evaluation
- Agentic systems prototyping
- Large-scale distributed systems
- Problem-solving in robotics/autonomous systems
- Software engineering fundamentals
Benefits
- Participation in company benefits programs
- Mentorship from industry leaders
- Exposure to Level 4 autonomous driving technology
- Hybrid onsite work arrangement
- Two-way learning and skill development opportunities
- Potential recruiting pipeline to full-time roles
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
- Can you describe a project where you used clustering or data analysis to identify patterns in complex datasets?
- How would you approach building an automated pipeline to detect anomalies in autonomous vehicle behavior?