ML Driver Refinement Intern — Driving Behavior Foundations

Waymo LLC; San Francisco (CA); Hybrid; USD 34,000 - 48,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

Bonus and equity opportunities

401(k) retirement plans

Job summary

Waymo LLC is offering an internship to contribute to data-driven driving behavior improvements. You will mine and curate driving data, and work with large language models and foundation models to support reasoning, decision making, and multi-modality generation.

The role emphasizes building robust data generation pipelines, designing experiments for model training, and advancing data-centric AI techniques within the Planner organization. Hybrid work options are available.

Qualifications

• You are currently enrolled in a graduate program (Master’s or PhD) in Computer Science or a related technical field.
• You have strong problem solving and programming skills in Python and/or C++.
• You have experience with model evaluation and understanding metrics.
• Some understanding of SQL is preferred, not required.
• Previous Internship experience is a plus.

Responsibilities

• Mine and curate dataset samples from large corpus of driving data.
• Leverage large language models and world foundation models for reasoning, decision making and multi-modality generation.
• Design and implement robust data generation pipelines for data generation.
• Design and evaluate experiments for model training.
• Designing robust data generation pipelines for model training.

Skills

Python

C++

Problem solving

SQL basics

Education

Graduate student (MS/PhD)

PhD preferred

Tools

Jax

PyTorch

Job description

Waymo LLC is offering an internship to contribute to data-driven driving behavior improvements. You will mine and curate driving data, and work with large language models and foundation models to support reasoning, decision making, and multi-modality generation.

The role emphasizes building robust data generation pipelines, designing experiments for model training, and advancing data-centric AI techniques within the Planner organization. Hybrid work options are available.