- Location
- Mountain View, CA, USA · Mountain View (US-MTV-EMF680)
- Workplace
- Remote, Hybrid, Onsite
- Type
- Internship
- Seniority
- Internship
- Education
- PhD
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.
The mission of the Waymo AI Foundations 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. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.
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:
- Design and conduct experiments on large-scale generative or foundation model training recipes
- Analyze model evaluation metrics to identify performance bottlenecks and optimization strategies
- Collaborate with researchers and engineers to integrate novel techniques into production training pipelines
You have:
- Currently enrolled in a PhD program in Computer Science, AI, Robotics, or a related quantitative field
- Solid background in deep learning, transformer architectures, and generative modeling
- Proficiency in Python and deep learning frameworks (PyTorch, JAX, or TensorFlow)
We prefer:
- Publications at top-tier AI/ML conferences (NeurIPS, ICML, ICLR, CVPR, ECCV, ICCV)
- Experience with distributed training across multi-node GPU/TPU clusters
- Familiarity with autonomous driving perception, prediction, or planning problems
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.