2025 Summer Intern, MS/PhD, Scalable ML Training Infrastructure
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.
Waymo interns work with leaders in the industry on projects that deliver significant impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skillset. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship!
You will:
- Scale distributed ML training frameworks to large clusters with thousands of accelerators
- Build mathematical models and conduct real experiments to analyze performance bottlenecks
- Improve distributed training efficiency by jointly optimizing communication and computation with cutting-edge technologies on ML runtime and compilers
You have:
- Progressing towards MS or PhD in Computer Science or related technical field.
- Python/C++ coding skills
- Familiarity with internals of ML frameworks (JAX, TensorFlow, PyTorch) and distributed training algorithms
- Experience with basics and algorithms of linear algebra, such as multi-dimensional MatMul and matrix calculus.
- Knowledge of deep learning models and optimization
We prefer:
- Familiarity using ML accelerators (GPU/TPU) with ML Compilers (TensorRT, XLA, etc.)
- Prior work on cloud computing platforms (AWS, Azure, GCP)
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.