2025 Summer Intern, MS/PhD, Research - Simulation Agents
London, United Kingdom
Internship Entry-level / Junior GBP 41K - 60K
Waymo
Waymo—formerly the Google self-driving car project—makes it safe and easy for people & things to get around with autonomous vehicles. Take a ride now.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.
The mission of the Waymo Research team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. Research areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.
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:
- Make fundamental contributions to simulation based evaluation of the Waymo Driver.
- Develop controllable & realistic simulation agents, and deploy them in the Waymo Simulator.
- Develop adversarial agents for more efficient simulation based evaluation.
You have:
- Currently pursuing a MS or PhD degree in Computer Science, Machine Learning, Robotics, or a related technical field.
- Proficient in Python and Tensor Manipulation (using NumPy / JAX / TensorFlow / etc.).
- Experience with Machine Learning and Robotics.
We prefer:
- Experience with Reinforcement Learning, Latent Variable Modeling, or Hidden Markov Models.
- Experience with Probabilistic Modelling (using Tensorflow Probability / Pyro / Stan / etc.).
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.
At Waymo, we don't just accept differences - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know.
#LI-Hybrid
The expected annual pay 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.
Masters Pay£41,000—£41,000 GBPThe expected annual pay 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.
PhD Pay£60,000—£60,000 GBPTags: Autonomous Driving Bayesian Computer Science Generative modeling JAX Machine Learning NumPy PhD Python Reinforcement Learning Research Robotics TensorFlow
Perks/benefits: Career development
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