Waymo-posted 16 days ago
$136,000 - $173,000/Yr
Full-time • Mid Level
Hybrid • Mountain View, CA
1,001-5,000 employees
Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

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. The Labeling Platform Team creates data solutions to power groundbreaking research and development during all stages of the ML Lifecycle: pretraining, supervised fine-tuning, reinforcement learning, etc. The labeled data that the team produces is used to directly enhance and evaluate the Waymo Driver as well as the vast variety of models that power other parts of the business. In this hybrid role you will report to a Technical Lead Manager/Staff Software Engineer.

  • Build state of the art labeling infrastructure to enable production of labeled datasets.
  • Improve the "data flywheel" end to end efficiency through automation and monitoring.
  • Work with the labeling operations teams to hillclimb on process efficiencies and build tooling to manage large workforces and distribute tasks effectively.
  • Bachelor's degree in Computer Science, Engineering, or related field, and 3+ years equivalent experience
  • Experience developing data annotation/review tools. EG: Labeling for ML, Content Reviews for Trust and Safety, etc.
  • Experience building API servers, web backends.
  • Experience building, optimizing, debugging, and maintaining large scale data processing pipelines.
  • Proficiency in Typescript and/or Frontend frameworks (Angular, ReactJS).
  • Experience in developing diverse data annotation tooling and infrastructure.
  • Knowledge of the application of labeled datasets within the full ML ecosystem.
  • Experiencing programming using C++, Python.
  • Hands-on experience with LLM/GenAI-based products.
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