Job description

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. This role follows a hybrid work schedule and reports to a Software Tech Lead Manager. You will: Own and drive the roadmap for ML-powered pickup and dropoff features, from problem definition through launch, in partnership with PM, UX, data science, and other commercialization engineering teams Train, evaluate, and deploy ML models for occupancy detection, rider-vehicle interactions, pullover selection, and lost and found Design fallback systems that cascade between onboard and offboard models based on latency, confidence, and connectivity Build distributed systems that span vehicles, cloud services, and rider apps, and that handle intermittent and inconsistent connectivity well Work across the stack (data pipelines, model serving, backend services, and client integration) to ship end-to-end, user-facing features Define success metrics and use offline evaluation, simulation, and live experiments to measure impact on service quality and rider experience You have: BS degree in Computer Science or equivalent practical experience 5+ years of software engineering experience, including building and deploying ML models into production Experience building backend distributed systems We prefer: Experience with C++ MS in Computer Science, or equivalent practical experience Experience in developing machine learning models, infrastructure, and pipelines Experience deploying models on-device or on edge hardware with compute and latency constraints Track record of owning ambiguous, user-facing problems end-to-end and setting your own technical direction Experience in autonomous vehicles or robotics Disclosure for WA Based & Remote Roles: In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include: Health, dental, vision, life, disability insuranceRetirement Benefits: 401(k) with company matchPaid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employmentSick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks Baby Bonding Leave: 18 weeks Holidays: 13 paid days per year US Remote Only: Please note that Waymo may not be able to employ remotely in all US locations. Please speak with your recruiter about your preferred location for remote work when you begin the interview process. 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

Requirements

Must-haves

Own and drive the roadmap for ML-powered pickup and dropoff features, from problem definition through launch, in partnership with PM, UX, data science, and other commercialization engineering teams
Train, evaluate, and deploy ML models for occupancy detection, rider-vehicle interactions, pullover selection, and lost and found
Design fallback systems that cascade between onboard and offboard models based on latency, confidence, and connectivity
Build distributed systems that span vehicles, cloud services, and rider apps, and that handle intermittent and inconsistent connectivity well
Work across the stack (data pipelines, model serving, backend services, and client integration) to ship end-to-end, user-facing features
Define success metrics and use offline evaluation, simulation, and live experiments to measure impact on service quality and rider experience
BS degree in Computer Science or equivalent practical experience
5+ years of software engineering experience, including building and deploying ML models into production
Experience building backend distributed systems
Experience with C++
MS in Computer Science, or equivalent practical experience
Experience in developing machine learning models, infrastructure, and pipelines
Experience deploying models on-device or on edge hardware with compute and latency constraints
Track record of owning ambiguous, user-facing problems end-to-end and setting your own technical direction
Experience in autonomous vehicles or robotics
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

Nice-to-haves

US Remote Only: Please note that Waymo may not be able to employ remotely in all US locations. Please speak with your recruiter about your preferred location for remote work when you begin the interview process.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlmachine learning

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off