PhD ML Intern - Predictive Planning for Autonomous Driving

Waymo LLC; Mountain View (CA); On-site; USD 97,000 - 138,000; Full time

Benefits offered by this job

Housing/relocation bonus

Health, dental, vision insurance

Intern events and networking

Free meals on site

Google shuttles access

Onsite gym

Job summary

Waymo LLC is seeking a PhD candidate to join our team focused on predictive planning for the Waymo Driver. You will research and implement advanced generative models, run experiments, and deliver robust code working closely with researchers and engineers.

The role emphasizes deep learning, reinforcement learning, and practical ML tooling (TensorFlow, JAX, PyTorch) within a robust autonomous driving research environment. Onsite perks support collaboration and learning.

Qualifications

• Currently pursuing a PhD in Computer Science, ML, Robotics, or related field.
• Experience with deep learning or reinforcement learning.
• Hands-on experience with modern deep learning libraries (TensorFlow, JAX, PyTorch) and programming (Python, C/C++).
• Strong analytical and debugging skills.

Responsibilities

• Research, implement, and evaluate state-of-the-art generative models for planning and predictions using JAX.
• Conduct machine learning model experiments.
• Product high-quality, thoroughly tested code.
• Collaborate with research, product, and engineering teams to introduce new research concepts.

Skills

Deep learning

Reinforcement learning

Python programming

Education

PhD in Computer Science or related field

Tools

TensorFlow

JAX

PyTorch

Job description

Waymo LLC is seeking a PhD candidate to join our team focused on predictive planning for the Waymo Driver. You will research and implement advanced generative models, run experiments, and deliver robust code working closely with researchers and engineers.

The role emphasizes deep learning, reinforcement learning, and practical ML tooling (TensorFlow, JAX, PyTorch) within a robust autonomous driving research environment. Onsite perks support collaboration and learning.