Sr. Software Engineer, Marketplace ML Platform

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 Platform team is part of the Marketplace engineering: we provide specialized business platforms supporting Marketplace ML and Optimization products. We own and host core ML models used throughout the Marketplace; we automate all parts of the model life cycle, such as feature engineering,  training workflows and inference services; we are working on next-generation Marketplace Simulation system capable to run high-fidelity virtual experiments; we also streamline diverse Marketplace Experimentation practices with the goal of providing unified user-friendly Experimentation platform.

You will:

• Implement and scale the core economic engine for Waymo's ride-hailing commercial services.
• Develop high-level infrastructure code for automatically training and deploying sophisticated optimization and prediction ML models to make real-time decisions for pricing, matching, and positioning.

You have:

• BS degree in Computer Science or equivalent practical experience.
• 4+ years of experience programming in backend coding languages such as Java or C++.
• Experience in building backend platforms supporting multiple product use-cases/services. 
• Prior Machine Learning Engineering experience in Python using mature ML frameworks such as TensorFlow, PyTorch or Keras.

We prefer:

• MS in Computer Science, or equivalent practical experience.
• Experience building and deploying ML / Optimization models into production environments.
• Experience developing ML data pipelines and ML workflow automation code on top of a mature ML infra. 
• Experience working at another Ride hailing or Marketplace company.
• Coursework background in ML and Optimization.