Staff Software Engineer, Fleet Optimization

Waymo•San Francisco, CA

About The Position

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.

Requirements

BS degree in Computer Science or related field.
5+ years of direct coding experience.
Backend or infrastructure preferred.
Experience with backend coding languages: C++, (secondary Python).
Professional experience building and analyzing quantitative software systems such as those involving algorithmic optimization, machine learning, or large-scale data analytics.

Nice To Haves

Experience implementing algorithms for multidimensional systems informed by practical knowledge in any of the fields of dynamics (system response, mechanics, system modelling) , optimization (gradient descent, linear algebra, filtering), control (linear, state space, stochastic, feedback control), operations research (constraint optimization, Linear programming) and/or implementing design patterns.
Passion for working in cross functional environments that include nontechnical stakeholders
Familiarity with Google infrastructure (e.g. Flume, Borg, Protocol Buffers, OnePlatform) or the equivalent non-Google technologies
Experience with operations tooling, developer productivity, or developer tools
Strong bias for action.

Responsibilities

Algorithm development, system design, and software implementation to solve multi-disciplinary problems at the intersection of computer science, optimization, and fleet management.
Instrument systems and analyze complex datasets in order to understand behaviors, troubleshoot problems, identify opportunities, and evaluate hypotheses and counterfactual scenarios.
Evaluate and reason about optimization and forecasting system performance, including sensitivity to inputs, fidelity of output actuations, and interactions with other automated and human systems.
Build, evolve, own, and operate mission-critical tools and systems responsible for the continuous optimization of fleet operations.
Collaborate with Depot Operations, Product, UX, Data Science, and other Engineering teams to develop and improve automated systems, operational processes, and documentation as business needs grow and evolve.