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Staff Machine Learning Engineer, Perception, Sensor Pipelines

Mountain View, California, United States. San Francisco, California, United States Full-Time Software Engineering 4431

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Staff Machine Learning Engineer, Perception, Sensor Pipelines

  • 4431
  • On Site
  • Mountain View, California
  • San Francisco, California
  • Software Engineering
  • Full-Time
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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.

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 Sensor Pipelines team applies sensor fusion and ML approaches to address critical challenges in Perception; like detections of Collisions, Antagonistic Behaviors like Vandalism, Sensing Occlusions, etc. Our work involves cutting-edge research (Gen AI) to solve real-world problems and requires close collaboration with onboard teams across Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to develop sophisticated models and techniques at scale. For this specific position, we are seeking an experienced MLE to be our data TL, build robust data pipelines and data flywheel for the team, through collaboration cross-team with Perception, Behavior, ML foundation and Simulation teams.

This role follows a hybrid work schedule and reports to a Technical Lead Manager.

You will:

  • TL the team to build data platforms for large-scale evaluation of the systems. Create data sets, recipes for human and machine labeling, methods and recipes for continuous logging, data intake, selection and incremental updates of models, stream eval data set curation, sampling & slicing, enable data-driven decision making, develop methods for logging, data mining and recipes for automated data collection/model update flywheels.
  • Define long-term strategy, develop roadmaps, and guide the team to execute projects from ambiguous requirements to high-impact deliverables.
  • Collaborate with team members in understanding their data needs & build infra solutions that solve their problems. Collaborate with the eval team to enable smooth, robust and efficient evaluation on top of the data platform.
  • Collaborate cross-team, exercise complete end-to-end ownership in delivering a robust and adaptable data platform jointly w/ collaborating teams. This platform will be capable of supporting rapid iteration and meeting the demanding timelines associated with Waymo's city expansions, enabling proactive problem-solving.

You have:

  • Bachelor’s in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
  • 8+ years of experience designing and building complex, scalable systems.
  • Demonstrated technical leadership in defining long-term strategy, developing roadmaps, and guiding teams to execute projects from ambiguous requirements to high-impact deliverables.
  • Demonstrated ability to work effectively across diverse teams and communicate technical concepts clearly.
  • Deep expertise in the evaluation of Machine Learning systems at scale, encompassing metrics design, rigorous experimentation, large-scale data analysis, and statistical methods.
  • Excellent problem-solving skills, clear technical communication, and a strong sense of end-to-end ownership.

We prefer:

  • Master’s or PhD in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
  • Familiarity with autonomous vehicle systems, particularly Perception, including typical data pipelines and evaluation processes.
  • Hands-on experience with data analysis, visualization, and triage tools & workflows, with a knack for identifying improvement areas.
  • Experience in designing and implementing efficient data processing workflows for large datasets.
  • Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI.
  • Experience with C++.

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
$238,000—$302,000 USD

We appreciate your interest in Waymo. Waymo is proud to be an equal opportunity employer, committed to creating a culture of belonging and maintaining a supportive workplace for all employees. We welcome applicants of all backgrounds, and employment decisions are based on a candidate’s qualifications, experience, and alignment with job requirements and business needs. 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, family status, pregnancy, 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 making sure our hiring process is accessible for all candidates. If you need assistance applying for a role or participating in the interview process due to a disability, 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?