Staff Machine Learning Engineer (TLM), Driver Understanding and Evaluation
Waymo · London, UK
- Location
- London, UK
- Level
- Staff
- Posted
- 14 July
About this role
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 DUE Machine Learning team will build and operate scalable machine learning and data systems, simulation workflow and insight tools, improve and speed up the evaluation and onboard developer journeys. It will combine expert human judgements and advanced machine learning models to deliver training and evaluation data for hundreds of metrics and components that make up the Waymo driver.
We are planning to set up a team in London UK to work with the teams in MTV and Oxford to build these foundation models out and to integrate them into several evaluation and training products. We are looking for researchers and software engineers who are passionate about developing machine learning techniques for the Evaluation systems on our autonomous vehicles, and have an incessant drive to improve the performance of our technology stack.
In this hybrid role, you will report to an Engineering Manager.
You will:
- Be part of a world class research engineering team to grow the state-of-the-art of ultra realistic AV simulations using foundation models
- Collaborate with teams in Waymo Oxford to use large models to improve sim realism
- Design experiments that push the frontiers of AV simulations
- Develop metrics that measure the realism of simulated worlds
- Train and evaluate large models and integrate them into the simulator and its downstream applications
- Help hire outstanding research engineers from diverse backgrounds
- Be a part of a collaborative research engineering team that takes research ideas and productionizes them
- 1+ years of people management experience
We prefer:
- 7+ years experience in applied Deep Learning
- 7+ years coding and design skills
- Experience solving complex production problems using state-of-the-art ML techniques
- Experience taking research to production
- Expertise in Data Analysis or Data Science
The expected base salary range for this full-time position 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. 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£155,000-£163,000 GBP
As published by Waymo. Applications are handled on their site.
Skills this posting mentions
About Waymo
On the journey to be the world's most trusted driver. With the Waymo Driver, we can improve mobility while saving thousands of lives. Download the Waymo One app and ride today. Waymo reaches out to candidates from official channels only (e.g. directly from @waymo.com email addresses, or through our recruiters or sourcers who are noted as such on LinkedIn). We do not contact candidates about career opportunities through instant messaging apps like Telegram, email addresses from domains other than waymo.com (such as Gmail addresses), direct messages on Twitter, Facebook, and Instagram, or text messages. Visit waymo.com to check out our official job listings.
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Paste your career in once. Every application after that is written for you.
Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
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