Staff Software Engineer, Data-Driven Behaviors
Job Summary
The Planner Reasoning Team at Waymo is seeking a skilled Applied Machine Learning Engineer to lead and develop data pipelines that power ML solutions for the Waymo Driver's decision making and motion planning. This role requires experience in data shaping, feature engineering, loss/reward shaping, finetuning, and model evaluation.
Responsibilities
- Lead and develop data pipelines for ML solutions
- Quickly prototype ideas to improve data pipelines and conduct model finetuning
- Integrate and deploy ML models on the fleet, conducting end-to-end validation and enabling on-field monitoring
- Collaborate closely with partner teams such as perception, research, simulation, and evaluation
- Mentor engineers in leading adoption of data-primary approaches for solving reasoning problems
Requirements
- Experience in applied machine learning: data shaping, feature engineering, loss/reward shaping, finetuning and model evaluation
- Eval experience: contributing to scalable eval workflows and building metrics for ML models
- Proficiency in dealing with large scale models and datasets
- High quality API design with an eye towards eval and data-driven techniques
- Experience with working and solving design problems that cut across multiple components
Qualifications
- PhD, Masters or Bachelors degree in Computer Science, Machine Learning, Robotics, or a related field
- Experience with Large Language Models (LLM), Vision Language Models (VLM), deep learning or reinforcement learning
- Experience in the autonomous driving domain, including areas like motion planning or perception
- Proficiency in C++, Python, and SQL
Benefits
The Waymo Driver offers a comprehensive benefits package including a discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
Pay
The expected base salary range for this full-time position across US locations is $251,000—$310,000 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level.