Staff Machine Learning Engineer, Model Optimization

Mountain View, CA, United States

Staff Machine Learning Engineer, Model Optimization Mountain View, California, United States Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.

Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you're a software engineer or researcher who's curious and passionate about Level 4 autonomous driving, we'd like to meet you.

The ML Platform team at Waymo provides a set of tools and technologies to support and automate the lifecycle of the machine learning workflow, including feature and experiment management, model development, debugging & evaluation, optimization, deployment, and monitoring. These efforts have resulted in making machine learning more accessible to teams at Waymo, including Perception, Planner, Research and Simulation, ensuring greater degrees of consistency and repeatability, and addressing the "last mile" of getting models into production and managing them once they are in place. We work hand in hand with machine learning experts in all parts of the company as well as our collaborators across Alphabet.

We are looking for a staff engineer with model optimization expertise to help us improve compute performance on our car. You'll work across the entire ML stack from models, to ML frameworks/libraries, to different HW platforms. You will collaborate with the world-class scientists and engineers in Waymo, Google, Deepmind and will be pleasantly challenged with the state-of- art-model compression technologies. Non-exhaustive examples of the types of work you will work on:

Lead the collaboration with the world-class Waymo ML scientists in perception, planner, research and simulation. Build productive relationships and understand their models. Identify opportunities in both systems and models to make ML workloads faster.

Lead projects from proposals, through goals and execution, to results. Lead and mentor junior engineers.

Deep dive into the full stack of ML software stack. Analyze the ML workload performance. Apply model optimization, efficient deep learning techniques and ML software improvements.

Collaborate on foundation models and ML System with external partners such as CoreML, Google Brain and Deepmind.

At a minimum, we'd like you to have:

M.S. in CS, EE, Deep Learning or a related field

2+ years of experience as a technical lead

3+ years of experience on model optimization or efficient deep learning techniques

Strong Python or C++ programming skills

Thorough understanding of key ML system challenges and trade-offs.

Solid experience with designing, training and debugging deep learning models to achieve the highest scores/accuracies.

It's preferred if you have one of the following:

PhD in CS, EE, Deep Learning or a related field.

Proven track record on efficient deep learning and/or model optimization techniques with foundation models.

Deep knowledge on system performance, GPU optimization or ML compiler.

5+ years of experience on model optimization or efficient deep learning techniques

While at Waymo, you will enjoy benefits that cover...

Health and wellness: Our people are at the heart of everything we do. At Waymo, you can enjoy top-notch medical, dental and vision insurance, mental wellness support, a Flexible Spending Account (FSA), a Health Saving Account (HSA), and special wellness programs.

Financial wellness: Your financial peace of mind is important to us. At Waymo, we offer competitive compensation, bonus opportunities, equity, a generous 401(k) plan, 1-on-1 financial coaching, a 529 College Savings Plan and lots of other perks and employee discounts.

Flexibility and time off: Take the time you need to relax and recharge. Enjoy the flexibility to work from another location for four weeks per year. We support an on-site or hybrid work model and offer remote working opportunities, paid time off, bereavement, sick, and parental leave.

Supporting families: When it comes to growing your family or caring for your loved ones, you have our full support. Enhanced leave options include paid parental leave (birthing parent gets 24 weeks of paid leave with up to 4 weeks of additional leave before their due date, and non-birthing parent gets 18 weeks of paid leave), and 20 days of subsidized backup childcare or adult/elder care.. Access to fertility care or adoption support as you grow your family.

Community and personal development: At Waymo, you'll find a range of opportunities to grow, connect, and give back. We offer education reimbursement, personal and professional development, mentorship, and other ways to connect through Employee Resource Groups (ERGs), other internal groups, and even time off to volunteer.

Cool perks: Access to Google offices, cafes, wellness centers, massages, and so much more. To support your wellbeing at home, you can enjoy at-home fitness and cooking classes, and more.

#LI-Hybrid

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.

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 $226,000-$286,000 USD We appreciate your interest in Waymo. Waymo is an equal employment opportunity employer, committed to maintaining a supportive and inclusive workplace for all employees. Waymo does not discriminate against, and prohibits harassment of, any applicant or employee based on race, color, sex, sexual orientation, gender identity, religion, national origin, age, disability, military status, genetic information or any other basis protected by applicable law. Waymo will also consider for employment qualified applicants with criminal records in accordance with applicable law. Waymo is committed to ensuring equal opportunity for qualified individuals with disabilities. If you are an individual with a disability and require an accommodation to participate in the application or interview process, please let the recruiting team know or email [email protected]. (This email address is intended to be used only for requesting accommodations as part of the application process. Other inquiries will not receive a response.)