Senior Software Engineer, Training Efficiency
Waymo · Mountain View, CA · Sys Intel and Machine Lrng (SQT)
About this role
Waymo is hiring a senior-level Software Engineer based in Mountain View, CA (hybrid). The posting calls out experience with Python, TensorFlow, Distributed Systems, System Design and roughly 5+ years of relevant work. Listed education preference: a bachelor's degree or equivalent. Compensation is listed at $238,000–$302,000 per year.
- Role
- Software Engineer
- Function
- software engineering
- Level
- senior
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Mountain View, CA
- Work mode
- Hybrid
- Experience
- 5+ 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 Waymo ML Infrastructure team works with Research and Production teams to develop models in Perception and Planning that are core to our autonomous driving software. We help our partners by offering the best solutions for the entire model development lifecycle. These solutions are developed in close collaboration with teams at Google. They are geared towards both scaling models and solving problems unique to ML for autonomous driving. You will improve the runtime efficiency of input data pipelines for large-scale training workloads. This is a unique opportunity to work on ML systems and improve on our model training processes.