Waymo
2025 Summer Intern, PhD, Data Science - Simulation
Waymo, Mountain View, California, us, 94039
Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ 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.
Waymo interns work alongside leaders in the industry on projects that deliver significant impact to the company. We believe learning is a two-way street: leveraging 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:
We use simulation to measure our performance and safety across a wide variety of metrics. Given the vast amount of data we have at Waymo and the rapid cadence we would like to update our estimates of performance, we have to be adaptive and sophisticated in how we choose which simulations to run at a regular cadence. You will work on scaling a custom optimization algorithm we use in the Simulation platform to choose which simulations we run. The work will involve fluency in numerical techniques as well as distributed optimization. This is a high-impact project that directly affects a variety of teams at Waymo.
You have:
Currently enrolled in a PhD program
The intern should be very familiar with PhD-level optimization techniques and literature - namely distributed convex optimization techniques.
Coding fluency in C++ and Python
Numerical algorithms
PhD level optimization techniques (distributed convex optimization)
We prefer:
In addition to optimization, it is recommended that the intern also have a background in:Statistics at the masters/PhD level, particularly importance sampling techniques
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 PhD Pay $60.10—$60.10 USD
Waymo interns work alongside leaders in the industry on projects that deliver significant impact to the company. We believe learning is a two-way street: leveraging 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:
We use simulation to measure our performance and safety across a wide variety of metrics. Given the vast amount of data we have at Waymo and the rapid cadence we would like to update our estimates of performance, we have to be adaptive and sophisticated in how we choose which simulations to run at a regular cadence. You will work on scaling a custom optimization algorithm we use in the Simulation platform to choose which simulations we run. The work will involve fluency in numerical techniques as well as distributed optimization. This is a high-impact project that directly affects a variety of teams at Waymo.
You have:
Currently enrolled in a PhD program
The intern should be very familiar with PhD-level optimization techniques and literature - namely distributed convex optimization techniques.
Coding fluency in C++ and Python
Numerical algorithms
PhD level optimization techniques (distributed convex optimization)
We prefer:
In addition to optimization, it is recommended that the intern also have a background in:Statistics at the masters/PhD level, particularly importance sampling techniques
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 PhD Pay $60.10—$60.10 USD