2027 Summer Intern, BS, Software Engineer, Model Eval

Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you. 

The subteam for this role will be:

The Model Eval team has a lot of projects that evolve quickly. We will help the Intern find a project that matches their skill set during the internship. Possible projects include:

• Eval pipeline optimization (orchestration level): Finding opportunities to decrease e2e execution cost by reducing overhead or increasing parallelism in jobs
• Eval pipeline optimization (model level): Improving eval workload efficiency by improving exported model efficiency in CPU or TPU export configurations
• Pipeline observability: Providing insights and high level metrics on pipeline runtime and success rate
• LLM integration: Finding better ways to integrate agents with eval workflows. This could be making it easier for agents to run evals accountably, or making it easier for agents to contribute maintainable code to the eval codebase

Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship!

• Reading/writing pipeline and implementation code
• Profiling and understanding slowness within distributed systems
• Building custom harnesses to isolate components of the system
• Querying existing logs and data sources for aggregate statistics

• Currently pursuing a Bachelor’s degree in software engineering or a related field
• Working knowledge of Python
• Understanding of ML fundamentals of training and evaluating models
• The ability to use agents for learning and implementation, and the wisdom to know when each is appropriate

• Distributed systems analysis or optimization
• Model performance techniques like sharding, quantization, and batching
• Working knowledge of C++