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.

Machine Learning models are at the core of Waymo's fully autonomous driving technology. Our models allow 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 perception, planning and control while collaborating with hardware and systems engineers. If you're curious and passionate about Level 4 autonomous driving, we'd like to meet you.

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:

• Design and implement CUDA C++ kernels for tasks such as graph processing, tree traversal, and raw sensor data preparation.

• Conduct performance profiling of existing critical path workloads to identify bottlenecks and propose improvements.

• Prototype and evaluate novel approaches for accelerating existing CPU workloads to GPU.

You have:

• Currently enrolled in a Master's or PhD program focused on High-Performance Computing, GPU Architecture, Systems, or a related field.

• Strong understanding of CUDA C++ and parallel algorithm design.

• Experience with performance with CPU/GPU profiling tools like Nsight Compute, pprof, and Perfetto.

We prefer:

• Prior experience in GPGPU optimization.

• Experience with hardware-software co-design.

• Knowledge of GPU microarchitecture.

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 Masters Pay**$70—$70 USD**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**$85—$85 USD**