Staff Machine Learning Engineer

Role Description

The Driver Understanding and Evaluation (DUE) team at Waymo is developing rich metrics for understanding the behavior of the Waymo Driver in the real world, and technologies such as context and scene analysis to understand driving, understanding and augmenting real world driving data to generate rare driving events, build large scale data infrastructure, improve components such as agents and a realistic simulator. These technologies come together to drive the overall technical strategy and methodology used to evaluate the behavior of the Waymo Driver.

The DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo driver. We are looking for researchers and software engineers who are passionate about developing machine learning techniques for the Evaluation systems on our autonomous vehicles, and have an incessant drive to improve the performance of our technology stack.

You will:

• Lead the development of cutting edge Deep Learning and machine learning models to enhance human-led triaging and introduce automation for high-volume workflows.
• Design and build Gen AI LLM/VLM solutions for self driving car behavior analysis and anomaly detection.
• Proactively monitor and assimilate best practices from within Alphabet and the broader industry to develop a Reinforcement Learning from human preference-based data collection and evaluation system.
• Enhance User Feedback Analysis, collaborate seamlessly with product and business teams to design and implement tools for multi-label classifications, sentiment assessment, comment summarization, root cause analysis and trend analysis of rider feedback.
• Oversee the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles.
• Drive technical direction, and provide technical inputs and guidance to the team.
• Work closely with PMs and TPMs to help define product requirements and align the technical agenda with the company's business objectives.
• Collaborate closely with multiple teams (e.g., Prediction, Planning, Research), other technical leads, and senior leaderships across Waymo to deliver on key strategic efforts.

Qualifications

• B.S. in Computer Science, Robotics, Machine Learning, similar technical field of study, or equivalent practical experience.
• 7+ years of experience with hands-on experience in machine learning projects.
• Strong coding experience in C++ and/or Python.
• Experience in at least one of: Foundational Models, VLM, Deep Learning.
• Experience with ML frameworks such as TensorFlow, PyTorch, Hugging Face's transformers, along with expertise in deep learning models and ML deployment at scale.

Requirements

• M.S. or Ph.D. degree Computer Science or related quantitative field with a specialization of machine learning (preferred).
• 10+ years of experience with hands-on experience in machine learning projects (preferred).
• Deep learning experience with Transformers (preferred).
• Gen AI LLM/VLM experience (preferred).
• Experience with building tools for applied machine learning, including MLOps, evaluation/validation techniques, and model performance optimization (preferred).
• Large-scale data processing and analytical skills (preferred).

Benefits

• Waymo employees are eligible to participate in Waymo’s discretionary annual bonus program.
• Equity incentive plan.
• Generous Company benefits program, subject to eligibility requirements.

Salary Range

The expected base salary range for this full-time position across US locations is $238,000 — $302,000 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.