2027 Summer Intern, PhD, Planner Machine Learning
About this role
Researching, designing, and implementing novel deep learning architecture, multi-task loss formulations, and preference ranking objectives in Python and Jax forms the core daily work for the Planner Machine Learning intern. Waymo develops autonomous driving technology through its Software Engineering team, which builds the brains of the Waymo Driver to perceive the environment and make safe driving decisions. Interns partner with industry leaders on impactful projects, utilizing distributed TPU infrastructure to train and diagnose large-scale neural networks while evaluating models across open-loop and closed-loop benchmarks.
This PhD internship exists to bring advanced research talent into the organization, serving as a key part of the technical culture and recruiting pipeline. Candidates pursuing a terminal degree who enjoy solving complex technical challenges in deep learning and robotics will thrive in this environment. The position is structured as a hybrid onsite opportunity based in San Francisco, California.
What you will do
- Research, design, and implement novel deep learning architecture, multi-task loss formulations, and preference ranking objectives in Python and Jax for the Large Selection model.
- Train and diagnose large-scale neural networks utilizing distributed TPU infrastructure.
- Analyze training dynamics, gradient conditioning, and representation quality during model development.
- Evaluate trained models across open-loop and closed-loop benchmarks to assess performance.
- Triage real-world driving scenarios to connect mathematical modeling choices with physical vehicle behavior.
What you need
- Currently pursuing a Ph.D. in Machine Learning or a related quantitative field.
- Demonstrate strong hands-on proficiency in Python along with at least one modern deep learning framework such as JAX or PyTorch.
- Possess a solid mathematical foundation in deep learning, optimization, loss formulation, and empirical model diagnostics.
- Bring experience in designing, running, and analyzing rigorous machine learning experiments on large-scale datasets.
Nice to have
- Track record of first-author publications at top-tier ML, robotics, or vision venues including NeurIPS, ICML, ICLR, CoRL, ICRA, or CVPR.
- Experience with transformer architectures, post-training/preference alignment, or sequential decision making.
- Familiarity with autonomous driving and motion planning.
- Experience with C++ or navigating large-scale production ML codebases and distributed data pipelines.
Benefits
- Eligible to participate in the Company's generous benefits programs, subject to eligibility requirements.
Skills and tech stack
Questions candidates ask
What is the work location and remote policy for this internship?
This will be a hybrid onsite internship position located in San Francisco, California.
What is the compensation for this role?
The expected hourly rate for this full-time position is $85 USD.
How does the application and hiring process work?
Resumes are accepted on a rolling basis until the role is filled. To be in consideration for multiple roles, candidates need to apply to each one individually and are asked to apply to the top 3 roles of interest.