Machine Learning Engineer, Marketplace Pricing
waymo · MountainView, CA, United States ·
- Employment
- Full time
- Category
- ML ai
- Experience
- 4+ years
- Company size
- 1000+
- Salary
- USD 175,000 – 215,000 / year
Designs and deploys real-time dynamic pricing algorithms for an autonomous ride-hailing marketplace, balancing supply, demand, and profitability using ML and distributed systems.
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.
TaaS (Transportation as a Service) is responsible for building an amazing user experience and business around the Waymo Driver. We are responsible collectively for Growth, Territory Expansion, Service Quality (including pickup, dropoff and routing), Marketplace (pricing, positioning, matching), and Partnerships / B2B(2C) monetization.
The Marketplace team builds the core decision systems that keep Waymo running smoothly. They design the algorithms that match riders to vehicles, optimize routing, balance supply and demand, forecast rider demand, and power dynamic pricing. Their work ensures the fleet stays efficient, riders get fast pickups, and the AV network operates safely and profitably across cities.
The Pricing team drives Waymo's revenue and business strategy by developing dynamic pricing algorithms that balance supply and demand in real-time. They build sophisticated models to set pricing, ensuring the service remains competitive and attractive to riders while maximizing fleet utilization and profitability across all operating markets. Their work is critical to navigating the complexities of ride-hailing dynamics, balancing user price sensitivity with operational efficiency.
You will:
- Implement and scale Waymo's core dynamic pricing engine to drive revenue and business strategy across all operating markets.
- Develop and deploy sophisticated ML models and optimization algorithms to set real-time pricing that balances supply, demand, and user price sensitivity.
- Build and maintain infrastructure for pricing experimentation, monitoring, and analysis to ensure service competitiveness and fleet profitability.
- Partner with product data scientists to productionize innovative pricing models, such as route-specific and session-based pricing solutions.
You have:
- BS degree in Computer Science or equivalent practical experience
- 4+ years of experience programming in backend coding languages
- Experience in building backend distributed system
- Experience in developing machine learning/optimization infrastructure and pipelines
- Prior experience building and deploying ML / Optimization models into production environments
We prefer:
- Experience in C++
- MS in Computer Science, or equivalent practical experience
- Experience in developing low latency, large-scale, user facing distributed systems
- Experience at another Ride hailing or Marketplace company
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.