Role at a glance
- Salary
- Not Disclosed
- Location
- CA. USA, California, United States Mountain View, California, United States
- Work arrangement
- Hybrid
- Employment
- Full-time
- Experience
- 10+ years of leadership experience in a large-scale machine learned production system Experience leading a post-training system that is used in production with 100M+ users, solving multiple targeted problems in parallel Experience building metrics, data, and flywheels for post-training applications Experience influencing without authority at the director and VP level or higher An ability to balance influencing day-to-day leadership on the ground with developing and influencing engineering strategy
- Education
- MS in computer science with an emphasis in machine learning or equivalent degree (PhD preferred)
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Role Summary
The Principal Software Engineer, Post Training will develop and lead a strategy for a next-generation post-training system for the Waymo Driver, building on existing large-scale models. The role advances onboard AI post-training and works across Waymo to support effective, scalable use of post-training.
What You'll Do
- Advance post-training techniques used in AI running onboard autonomous vehicles.
- Track post-training research and identify applications for Waymo's autonomous-driving challenges.
- Participate in the leadership community advancing Waymo's machine-learning stack.
- Partner with ML platform teams to develop platforms for scalable post-training.
- Work with teams to understand their needs and guide them toward effective post-training strategies.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Requires an MS in computer science with an emphasis in machine learning or equivalent degree, 10+ years of leadership experience in a large-scale machine-learned production system, experience leading a production post-training system used by 100M+ users while solving multiple targeted problems in parallel, experience building post-training metrics, data, and flywheels, and experience influencing director- and VP-level leaders without authority. Also requires balancing day-to-day leadership with engineering strategy.
Required
- MS in computer science with an emphasis in machine learning or equivalent degree
- 10+ years of leadership experience in a large-scale machine learned production system
- Experience leading a post-training system that is used in production with 100M+ users, solving multiple targeted problems in parallel
- Experience building metrics, data, and flywheels for post-training applications
- Experience influencing without authority at the director and VP level or higher
- An ability to balance influencing day-to-day leadership on the ground with developing and influencing engineering strategy
Preferred
- PhD
- Experience building a post-training platform from scratch
- Experience with utilizing ML in AV and/or other robotics applications
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.
Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you.
The Onboard Software team develops the critical software and machine learning models that power the Waymo Driver. Our systems enable the vehicle to perceive its surroundings, make safe driving decisions, and transport people to their destinations. With Waymo's fleet driving millions of miles every week, we operate at a scale that exposes our technology to a vast array of challenging real-world scenarios.
As Principal Software Engineer Post Training, you will play a key role in advancing the technology to power the Waymo Driver and especially help it scale to dramatically more miles and locations across the world. Your primary responsibility will be to develop and lead a strategy of a next-generation post-training system on top of existing large-scale models (whose development this role will also influence). Post training is already used in the onboard software system, but we believe that there is a significant opportunity to advance its impact, in line with the advancements within the AI community in other applications. Your role would be to figure out how to accomplish that goal in the challenging, highly impactful problem of autonomously driving a vehicle in the real world at large scale.
This role follows a hybrid work schedule and reports into the Onboard organization.
You will:
- Advance the state-of-the-art post-training techniques in the AI running on board the autonomous vehicle
- Keep up with post-training research and find the right applications for the unique problems at Waymo
- Participate in the leadership community advancing the ML stack across Waymo in general
- Partner with teams developing ML platforms to develop them for effective, scalable post-training
- Partner with teams not yet using post-training effectively to understand their needs and guide them to effective post-training strategies
You have:
- MS in computer science with an emphasis in machine learning or equivalent degree (PhD preferred)
- 10+ years of leadership experience in a large-scale machine learned production system
- Experience leading a post-training system that is used in production with 100M+ users, solving multiple targeted problems in parallel
- Experience building metrics, data, and flywheels for post-training applications
- Experience influencing without authority at the director and VP level or higher
- An ability to balance influencing day-to-day leadership on the ground with developing and influencing engineering strategy
We prefer:
- Experience building a post-training platform from scratch
- Experience with utilizing ML in AV and/or other robotics applications
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.
About the company
Waymo
Large Enterprise
Waymo is a leading autonomous driving technology company, originally a part of Google's parent company Alphabet Inc. Established in 2009, Waymo focuses on developing self-driving cars and innovative transportation solutions designed to enhance mobility and safety on the roads. By employing advanced artificial intelligence and machine learning algorithms, the company aims to revolutionize personal and shared transportation, making it more accessible and efficient. Waymo's efforts contribute significantly to the future of autonomous vehicles and the ongoing shift towards smart transportation systems.