Staff Tech Lead, Machine Learning Engineer, Perception
Waymo · Mountain View, California
- Location
- Mountain View, California, United States
- Level
- Staff
- Posted
- 12 January
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 Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the self-driving car, i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware.
In this hybrid role, you'll report to a Staff Technical Lead Manager.
You will:
- Lead the design and development of multi-sensor, multi-task model architectures for dense and complete scene understanding with a focus on key tasks including object detection, occupancy prediction, road understanding, and trajectory planning.
- Architect and develop the foundational modeling libraries and software powering model development and experimentation.
- Design and implement scalable core model components, including sensor encoders, sensor fusion modules, backbones, and temporal aggregation / memory blocks.
- Adapt SOTA ML technologies to unique compute requirements, leading optimizations for latency, throughput, and memory to operate efficiently within strict compute budgets.
- Drive rapid prototyping by building and maintaining flexible pipelines and development environments for fast iteration on novel model designs, enabling seamless integration of field advancements and in-depth analysis of model training dynamics and learned representations.
You have:
- Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
- 7+ years experience in Machine Learning and/or Computer Vision
- Strong expertise in Python and C++ and a solid software engineering background
- Experience with ML frameworks like PyTorch, JAX, or Tensorflow
We prefer:
- MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline
- Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI
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$251,000-$310,000 USD
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.
All 370 openings at WaymoOne click, then it is written
Apply to Waymo with a resume written for this role.
Queue Staff Tech Lead, Machine Learning Engineer, Perception and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Waymo’s form for you.
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.
- 25 sent a week, free
- No card
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Put this to work
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.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
Free, no card. Up to 25 applications sent a week, and nothing is sent until you say so.
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