2027 Summer Intern, MS/PhD, Software Engineer, Eval Data Infra
Waymo · Mountain View, United States · 10h ago
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 Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced data-minded software engineers to help us improve how we analyze and evaluate changes to the Onboard software stack (Planner, Perception, etc) and help us build the data platform and infrastructure to support ML launch evals for the Waymo Driver.
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:
- Develop data pipelines to generate high-quality ML and evaluation datasets, streamlining curation, sampling, and slicing for training and testing the Waymo Driver software
- Design and implement robust tools and infrastructure for data mining, exploration, and analysis to extract insights from large-scale datasets and drive data-driven decisions
- Architect, build, and maintain large-scale data platforms to process Waymo driving logs and simulation data, ensuring dataset generation is fresh, accurate, and complete
- Collaborate cross-functionally with Data Science and Quantitative Analytics teams to build data infrastructure solutions
You have:
- Currently pursuing graduate degree (Master's or PhD) in Computer Science, Software Engineering or a related technical field
- Distributed Systems: Hands-on experience with systems that ingest, store, transform, and output data at scale
- Programming Languages: Proficiency in C++ or Python within a production environment
- Communication: Strong technical communication and collaboration skills
We prefer:
- Experience with A/B experiment infrastructure
- Exposure to ad-hoc data analysis utilizing SQL
- Prior experience working within the autonomous vehicle (AV) industry
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 (These perks will only be applicable if the internship is on site)
- 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.