Job description

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. 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! You will: 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 You have: 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 We prefer: Distributed systems analysis or optimization Model performance techniques like sharding, quantization, and batching Working knowledge of C++ General Perks Help solve challenging problems with a direct impact on the company Competitive compensation packages with a housing/relocation bonus (if applicable) Medical, dental, and vision insurance Fun intern events and networking opportunities Onsite Perks Free breakfast, lunch, dinner, and snacks Free access to Google shuttles Onsite gym Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in. The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly Bachelors Pay $60 — $60 USD

Requirements

Must-haves

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
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++
General Perks
Help solve challenging problems with a direct impact on the company
Fun intern events and networking opportunities
Onsite Perks
Free breakfast, lunch, dinner, and snacks
Free access to Google shuttles

Nice-to-haves

Competitive compensation packages with a housing/relocation bonus (if applicable)

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

llmpythonml

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision