Hybrid PhD ML Intern — Synthetic Data & Foundations

Waymo LLC; San Francisco (CA); Hybrid; USD 97,000 - 138,000; Full time

Job summary

Waymo LLC in San Francisco is seeking a PhD intern to develop data generation and model training methods for autonomous driving research. You will build sampling tools, train models on synthetic and logged data, and present findings on synthetic data generation techniques.

This hybrid onsite internship offers exposure to cutting-edge ML in a safety-focused environment. The internship requires a PhD in progress inCS/ML/Robotics/EE with hands-on experience in PyTorch or Jax, and familiarity with

Qualifications

• Currently pursuing a PhD in Computer Science, Machine Learning, Robotics, Electrical Engineering or a related technical field.
• Familiarity with methods of sampling from large models.
• Experience with post-training methods such as SFT, RL, and preferences.
• Modern deep learning frameworks such as PyTorch and Jax.

Responsibilities

• Build tools for sampling, selecting, and discarding synthetic driving data with testable hypotheses of how that data will lead to improvement.
• Train and evaluate models with mixtures of synthetic and logged data.
• Present and write about methods for synthetic data generation and training.

Skills

PhD in CS/ML/Robotics/EE

Sampling from large models

Post-training methods (SFT/RL)

Education

PhD candidate

Tools

PyTorch

JAX

Job description

Waymo LLC in San Francisco is seeking a PhD intern to develop data generation and model training methods for autonomous driving research. You will build sampling tools, train models on synthetic and logged data, and present findings on synthetic data generation techniques.

This hybrid onsite internship offers exposure to cutting-edge ML in a safety-focused environment. The internship requires a PhD in progress inCS/ML/Robotics/EE with hands-on experience in PyTorch or Jax, and familiarity with