Senior Software Engineer/Data Scientist, Planner Evaluation

Mountain View, California, USA

Waymo

Waymo—formerly the Google self-driving car project—makes it safe and easy for people & things to get around with autonomous vehicles. Take a ride now.

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Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.

The Planner Evaluation team works on one of the key challenges in autonomous driving: measuring and improving the quality of the software that drives the car. We are looking for experienced software engineers and data scientists to help us understand and improve the performance of Waymo's ML and robotics systems, and to develop novel performance metrics and measurement techniques. If you are excited about leveraging a large volume of extremely rich data to improve core technology at the very heart of autonomous driving, this is the place for you! In this hybrid role, you will report to the Senior Manager of Planner Evaluation.

In this hybrid role, you will:

  • Develop signals to measure the performance of large scale machine learning models that power our self-driving car's behavior, using a range of techniques including statistics, math, physics, and machine learning.
  • Use simulation creatively to measure driving performance of novel ML algorithms.
  • Work closely with statisticians, machine learning engineers, and roboticists to develop novel solutions to open problems.
  • Build data pipelines for signal discovery, data labeling, feature extraction and metric computation based on large-scale simulations.
  • Create tooling for metric aggregation, reporting, and visualization that are tailored for behavioral evaluation.
  • Spin up continuous monitoring and validation of metric signals, anomaly detection and root cause identification.

We'd like you to have:

  • BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area
  • 5 years of industry experience 
  • Python, especially for modeling and/or statistical computing 
  • Experience with tools for large-scale parallel compute and data manipulation (Apache Beam, SQL)
  • Experience with evaluating the quality of machine learning prediction quality at scale.
  • Problem-oriented mindset instead of only a solutions-oriented approach

It's preferred if you have:

  • PhD in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area
  • 7+ years preferred
  • Comfort with writing production code in Tensorflow / JAX
  • Experience with large-scale parallel compute
  • Experience in robotics or with spatial data in another field 

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. 

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. 

Salary Range$192,000—$243,000 USD
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Tags: Autonomous Driving Computer Science Data pipelines JAX Machine Learning Mathematics ML models PhD Physics Pipelines Python Robotics SQL Statistics TensorFlow

Perks/benefits: Career development Equity / stock options Salary bonus

Region: North America
Country: United States

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