Machine Learning Engineer - Gen SWE

Waymo • Mountain View, CA

9d • $213,000 - $263,000 • Hybrid

About The Position

Waymo is hiring a Machine Learning Engineer for its Gen SWE team. The role focuses on ML-powered pickup and dropoff features, owning their roadmap from problem definition through launch in partnership with product management, UX, data science, and commercialization engineering teams. The engineer will train, evaluate, and deploy models for occupancy detection, rider-vehicle interactions, pullover selection, and lost and found; design fallback systems that select between onboard and offboard models; and build distributed systems across vehicles, cloud services, and rider apps that tolerate intermittent and inconsistent connectivity. The role spans data pipelines, model serving, backend services, and client integration to deliver end-to-end user-facing features. Success is measured using defined metrics, offline evaluation, simulation, and live experiments to assess service quality and rider experience.

The position follows a hybrid work schedule and reports to a Software Tech Lead Manager. It is a full-time position with an expected US base salary range of $213,000–$263,000. Actual pay depends on job-related factors and location. Employees may also be eligible for a discretionary annual bonus, equity incentive plan, and company benefits, subject to eligibility requirements.

Requirements

• Bachelor’s degree in Computer Science or equivalent practical experience.
• At least 5 years of software engineering experience, including building and deploying machine learning models into production.
• Experience building backend distributed systems.

Nice To Haves

• Experience with C++.
• Master’s degree in Computer Science or equivalent practical experience.
• Experience 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 technical direction.
• Experience in autonomous vehicles or robotics.

Responsibilities

• Own and drive the roadmap for ML-powered pickup and dropoff features from problem definition through launch, partnering with product management, UX, data science, and commercialization engineering teams.
• Train, evaluate, and deploy machine learning 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 across vehicles, cloud services, and rider apps that handle intermittent and inconsistent connectivity.
• Work across 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 effects on service quality and rider experience.

Benefits

• Health, dental, vision, life, and disability insurance.
• 401(k) with company match.
• 20 days of vacation per year, accruing at 6.15 hours per pay period for the first five years of employment.
• Sick time: 40 hours per year where statutory, and 5 days per event discretionary.
• Maternity leave (short-term disability plus baby bonding): 28–30 weeks.
• Baby bonding leave: 18 weeks.
• 13 paid holidays per year.
• Eligibility to participate in a discretionary annual bonus program and equity incentive plan, subject to eligibility requirements.
• Company benefits program, subject to eligibility requirements.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior