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Senior Machine Learning Engineer, Runtime & Optimization

Mountain View, California, United States Full-Time Software Engineering 2874

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Senior Machine Learning Engineer, Runtime & Optimization

  • 2874
  • On Site
  • Mountain View, California, United States
  • Software Engineering
  • Full-Time
  • Mid Career

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.

The ML Platform team at Waymo provides a set of tools 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 are looking for a Senior engineer with model optimization expertise to help us improve compute performance on our car. In this hybrid role, you will report to our Head of Model Optimization.

You will:

  • Work across the entire ML framework/compiler stack (e.g. JAX, XLA, Triton, and CUDA), and system-efficient deep learning models.
  • Deep dive into the whole stack of ML software stack, from custom ops, framework/ ML compiler, to low-level libraries.
  • Apply model optimization and efficient deep learning techniques to models and optimized ML operator libraries.

You have:

  • M.S. in CS, EE, Deep Learning or a related field
  • 3+ years of experience on model optimization or efficient deep learning techniques
  • Strong Python or C++ programming skills
  • Solid experience with designing, training and debugging deep learning models to achieve the highest scores/accuracies.

We prefer:

  • PhD in CS, EE, Deep Learning or a related field.
  • Deep knowledge on system performance, GPU optimization or ML compiler.
  • 5+ years of experience on model optimization or efficient deep learning techniques

#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. 

Salary Range
$192,000—$243,000 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 waymo-candidatesupport@google.com. (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.)

Some of our Benefits

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, gym membership, and special wellness programs.

Financial wellness

Your financial peace of mind is important to us. At Waymo, we offer competitive compensation, bonus opportunities, equity, employees provident fund, 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 26 weeks of paid leave for birthing parents and 18 weeks of paid leave for non-birthing parents.

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.

Ready to Apply?

 

Demographic Information (completion voluntary)

Waymo would greatly appreciate it if you could provide us with your identity information. Your individual identity data will not be accessible to recruiters, hiring managers or others who interview you. Instead, it is used in aggregate to track and report Equity, Inclusion, and Diversity (EID) progress. Answering these questions is entirely voluntary, and a decision not to answer will not be held against you. 

If you decide to provide demographic information, it will be recorded and maintained in a confidential file. Whatever your decision about providing this data, it will not be considered in the hiring process or as a basis for employment decisions. If you are offered and accept employment with Waymo, the information collected during the application and recruitment process will become part of your confidential employment record.

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