PhD ML Planner Intern – Autonomous Driving (Hybrid)

We Love AI Jobs; San Francisco (CA); Hybrid; USD 97,000 - 138,000; Full time

Job summary

Waymo is offering a PhD internship in San Francisco focused on developing the Large Selection model for autonomous driving. You will design and train models, then evaluate them against driving benchmarks and real-world scenarios.

You will research, design, and implement novel deep learning architectures in Python and JAX, train on distributed TPU infrastructure, and connect modeling choices to vehicle behavior.

Qualifications

• PhD student in ML or related quantitative field.
• Proficiency in Python and JAX.
• Strong foundation in deep learning, optimization and empirical model diagnostics.
• Experience designing, running, and analyzing ML experiments on large-scale datasets.

Responsibilities

• Design and implement deep learning architectures, loss formulations, and ranking objectives for Waymo’s Large Selection model.
• Train neural networks on distributed TPU infrastructure and analyze training dynamics and representation quality.
• Evaluate models on driving benchmarks and connect modeling choices to vehicle behavior.

Skills

Python

JAX

deep learning

neural networks

distributed TPU training

optimization

model evaluation

transformer architectures

Education

PhD in progress

Job description

Waymo is offering a PhD internship in San Francisco focused on developing the Large Selection model for autonomous driving. You will design and train models, then evaluate them against driving benchmarks and real-world scenarios.

You will research, design, and implement novel deep learning architectures in Python and JAX, train on distributed TPU infrastructure, and connect modeling choices to vehicle behavior.