Software Engineer - Fleet Optimization

3w3 weeks ago

Waymo

San Francisco, US · Full-time · $175,000 – $215,000

About this role

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. The Waymo Driver powers fully autonomous ride-hail service and has provided over ten million rider-only trips. This role focuses on fleet optimization to improve access to mobility.

You will design algorithms and implement software to solve multi-disciplinary real-world problems at the intersection of computer science, optimization, and fleet management. You will instrument systems and analyze data to understand behaviors, troubleshoot, and identify opportunities.

This role requires strong cross-team collaboration across technical teams (mobile app, cloud backends, Waymo Driver) and functional teams (operations, product, legal, policy, privacy). You will work on cross-cutting problems, making informed tradeoffs in system design around real-world system realities.

You will build, evolve, own, and operate mission-critical tools and systems that are business critical infrastructure. The ideal candidate is self-sufficient and product-minded, passionate about working in cross-functional environments with nontechnical stakeholders.

Requirements

BS degree in Computer Science or equivalent practical experience.
5+ years of direct coding experience (backend or infrastructure preferred).
Experience with backend coding languages: C++, secondary Python.
Experience implementing algorithms for multidimensional systems.
Practical knowledge in dynamics, optimization, control, operations research, 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).
Experience with operations tooling, developer productivity, or developer tools.

Responsibilities

Algorithm design and software implementation to solve multi-disciplinary real-world problems at the intersection of computer science, optimization and fleet management.
Make informed tradeoffs in system design around real world system realities in fleet optimization.
Instrument systems and analyze data to understand behaviors, troubleshoot, and identify opportunities.
Build, evolve, own, and operate mission-critical tools and systems.
Collaborate with Operators on the ground, Product, UX, data science, and other engineering teams to develop and deliver business critical infrastructure.