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Machine Learning Engineer - Labeled Data

Mountain View, California, United States Full-Time Software Engineering 3664

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Machine Learning Engineer - Labeled Data

  • 3664
  • 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 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 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 Labeling Platform Team creates data solutions to power groundbreaking research and development during all stages of model training: pretraining, supervised fine-tuning, reinforcement learning, etc. The labeled data that the team produces is used to directly enhance and evaluate the Waymo Driver as well as the vast variety of models that power other parts of the business.

You Will:

  • Build state of the art labeling tools to allow users to annotate the real world in 3D.
  • Build tooling that allows the Operations teams to manage large workforces and distribute tasks effectively.
  • Collaborate with ML practitioners to understand their data needs and translate those requirements appropriate label formats and labeling experiences that can be efficiently used by labelers.
  • Collaborate with UX teams to turn tooling mocks into productionized applications.
  • Integrate ML automation to increase human labeler quality and efficiency
  • Work with the human operations teams to hillclimb on process efficiencies.

You Have:

  • Bachelor's degree in Computer Science, Engineering, or related field, and 3+ years equivalent experience
  • Experience developing human labeling/review tools. EG: Labeling for ML, Content Reviews for Trust and Safety, etc.
  • Expertise in Typescript and Frontend frameworks
  • Experience in working with WebGL using Three.js or similar libraries.

Nice To Have:

  • Experience in developing human + ML interaction schemes to boost productivity and quality of label generation.
  • Experience in leveraging WebAssembly and/or WebWorkers for web browser performance optimizations.
  • Experiencing programming using C++.
  • Hands-on experience with LLM/GenAI-based products.

This position reports into an Engineering Manager

 

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
$170,000—$216,000 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?

 

To ensure thorough consideration of each application, candidates may submit up to 5 job applications within a 60-day period. We encourage you to carefully review job descriptions and apply to positions that best match your skills. Applications beyond this limit will not be considered.

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