Software Engineer, Onboard Reliability Infra
Waymo · Mountain View, CA · Sys Intel and Machine Lrng (SQT)
About this role
Waymo is hiring a mid-level Software Engineer based in Mountain View, CA (hybrid). The posting calls out experience with Python and roughly 3+ years of relevant work. Listed education preference: a bachelor's degree or equivalent. Compensation is listed at $170,000–$216,000 per year.
- Role
- Software Engineer
- Function
- software engineering
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Mountain View, CA
- Work mode
- Hybrid
- Experience
- 3+ years
- Education
- Bachelor's degree
- Department
- Sys Intel and Machine Lrng (SQT)
More roles at Waymo
Job description
from Waymo careersWaymo 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.
The Planner/Perception Reliability team builds out architectures, tools, and workflows to prevent, identify, and guide fixes of reliability issues.
The team focuses on reliability and is accountable for onboard software health while ensuring high development velocity.
In this hybrid role you will report to a Staff Software Engineer / Tech Lead Manager.
You will:
- Architect the backbone of onboard reliability: build the critical infrastructure and tooling ecosystem that ensures onboard software is robust and reliable by design.
- Develop a deep understanding of system behavior, implementing dense, low-noise metrics providing immediate insight into vehicle and fleet performance.