Senior Machine Learning Engineer (Infra), Driver Understanding and Evaluation

Waymo; Mountain View (CA); On-site; USD 213,000 - 263,000; Full time

Benefits offered by this job

Discretionary annual bonus

Equity incentive plan

Generous Company benefits program

Job summary

A leading autonomous driving technology company is seeking experienced researchers and software engineers to build scalable machine learning systems for evaluating driving behaviors. You will contribute to model training, collaborate cross-functionally, and optimize machine learning frameworks to enhance autonomous vehicle performance. The role requires a strong educational background in relevant fields, significant experience in machine learning infrastructure, and expertise in distributed techniques. The expected salary range is $213,000 — $263,000 USD.

Qualifications

• 5+ years in machine learning infrastructure includes developing, designing, and optimizing systems.
• Experience in large-scale machine learning systems from data to model.
• Strong expertise in distributed training techniques and optimization strategies.

Responsibilities

• Build scalable systems for training and fine-tuning large-scale models.
• Own complex systems with architectural direction meeting business objectives.
• Collaborate to derive performance requirements for large ML systems.

Skills

Machine Learning Infrastructure

Distributed Training Techniques

Machine Learning Tooling

Large-Scale Models

Education

M.S. or Ph.D. in Computer Science, Machine Learning, or related field

Tools

PyTorch

Tensorflow

Ray

Job description

Overview

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—the World's Most Experienced Driver—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

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.

Responsibilities

• Build scalable systems for training and fine-tuning large-scale models to evaluate interesting driving behaviors.
• Work at the intersection of data engineering, model development, and simulation. Provide guidance on architectural decisions and technical directions. Own large, complex systems, driving architectures that meet technical and business objectives.
• Contribute to the production and optimization of machine learning models aiming to assess Waymo's expansive fleet of vehicles that cumulatively travel millions of miles.
• Design and scale large distributed systems covering the ML lifecycle, supporting planet-scale dataset generation, model training, and evaluation.
• Collaborate cross-functionally to derive performance and system-level requirements for large ML systems. Translate product/business goals into measurable technical deliverables, ensuring system component alignment.

You have

• M.S. or Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience.
• 5+ years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model.
• A history of contributions to machine learning tooling and frameworks e.g. PyTorch, Jax, Tensorflow, Ray, or similar. The candidate should understand both the user facing API and the internal workings.
• Strong expertise in distributed training techniques, including gradient sharding and optimization strategies for scaling large models across ML accelerator profiling tools to uncover performance bottlenecks.

We prefer

• 7+ years in machine learning infrastructure such as developing, designing, scaling, training, deploying, and optimizing large-scale machine learning systems from data to model.
• Experience in the autonomous vehicles domain, robotics, or complex simulation environments.
• Familiarity with large-scale simulation platforms and their integration with ML training workflows.

Compensation and Benefits

The expected base salary range for this full-time position across US locations is listed below. 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.

Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range

$213,000 — $263,000 USD