MLE, Post-Training & Reinforcement Learning Frameworks
Mountain View, California, United States Full-Time Software Engineering 3891
MLE, Post-Training & Reinforcement Learning Frameworks
- 3891
- On Site
- Mountain View, California, United States
- Software Engineering
- Full-Time
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 Waymo ML Frameworks & Efficiency team partners closely with Research and Production teams across Waymo to develop and deploy models in Perception and Planning that are core to our autonomous driving software. We help our partners by offering the best frameworks for the entire model development lifecycle, including pre-training and post-training. They are geared towards both scaling models with efficiency and solving problems unique to ML for autonomous driving.
We are looking for engineers with ML system expertise to help us train and improve pre-trained models to be deployed into Waymo Driver, and potential future products. You’ll work closely with researchers and modeling engineers across the company, and tackle the challenges of large-scale reinforcement learning (RL), building systems that can scale across compute, data, and environments to improve model intelligence and alignment with human drivers.
You Will:
- Develop the core training system for adapting RL techniques to unprecedented scales and heterogeneous environments (i.e. CPU/GPU/TPU).
- Collaborate with cross-functional teams to integrate cutting-edge rollout strategies, policies, and RL algorithms (i.e. REINFORCE, DPO, PPO, etc.) into the system.
- Optimize the end to end RL training pipeline for efficient and scalable learners/actors, and low-latency distributed reply buffers for persisting data produced by the rollouts.
- Build robust evaluations, analyze experimental results and iterate quickly to improve model performance and training workflows.
- Stay current with the latest research in RL, Vision-Language-Action (VLA) models, and World models to inform and inspire new initiatives.
You Have:
- B.S. in Computer Science, Math, or 8+ years equivalent real-world experience.
- Proficient in distributed systems design with an understanding of ML efficiency.
- Experience with ML frameworks, including TensorFlow, JAX, XLA.
- Solid programming skills in Python and C++.
- Practical familiarity with profiling tools to uncover performance bottlenecks.
We Prefer:
- MS in Computer Science, Math
- Familiarity with post-training frameworks like TS/REX, Tunix, TorchRL, TRL, etc.
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.
We appreciate your interest in Waymo. Waymo is proud to be an equal opportunity employer, committed to creating a culture of belonging and maintaining a supportive workplace for all employees. We welcome applicants of all backgrounds, and employment decisions are based on a candidate’s qualifications, experience, and alignment with job requirements and business needs. Waymo does not discriminate against, and prohibits harassment of, any applicant or employee based on race, color, sex, sexual orientation, gender identity, religion, national origin, age, disability, military status, family status, pregnancy, genetic information or any other basis protected by applicable law. Waymo will also consider for employment qualified applicants with criminal records in accordance with applicable law. Waymo is committed to making sure our hiring process is accessible for all candidates. If you need assistance applying for a role or participating in the interview process due to a disability, please let the recruiting team know or email waymo-candidatesupport@google.com. (This email address is intended to be used only for requesting accommodations as part of the application process. Other inquiries will not receive a response.)
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Some of our Benefits
Health and wellness
Our people are at the heart of everything we do. At Waymo, you can enjoy top-notch medical, dental and vision insurance, mental wellness support, gym membership, and special wellness programs.
Financial wellness
Your financial peace of mind is important to us. At Waymo, we offer competitive compensation, bonus opportunities, equity, employees provident fund, and lots of other perks and employee discounts.
Flexibility and time off
Take the time you need to relax and recharge. Enjoy the flexibility to work from another location for four weeks per year. We support an on-site or hybrid work model and offer remote working opportunities, paid time off, bereavement, sick, and parental leave.
Supporting families
When it comes to growing your family or caring for your loved ones, you have our full support. Enhanced leave options include 26 weeks of paid leave for birthing parents and 18 weeks of paid leave for non-birthing parents.
Community and personal development
At Waymo, you'll find a range of opportunities to grow, connect, and give back. We offer education reimbursement, personal and professional development, mentorship, and other ways to connect through Employee Resource Groups (ERGs), other internal groups, and even time off to volunteer.
Cool perks
Access to Google offices, cafes, wellness centers, massages, and so much more. To support your wellbeing at home, you can enjoy at-home fitness and cooking classes, and more.
Health and wellness
Our people are at the heart of everything we do. At Waymo, you can enjoy top-notch medical, dental and vision insurance, mental wellness support, gym membership, and special wellness programs.
Financial wellness
Your financial peace of mind is important to us. At Waymo, we offer competitive compensation, bonus opportunities, equity, employees provident fund, and lots of other perks and employee discounts.
Flexibility and time off
Take the time you need to relax and recharge. Enjoy the flexibility to work from another location for four weeks per year. We support an on-site or hybrid work model and offer remote working opportunities, paid time off, bereavement, sick, and parental leave.
Supporting families
When it comes to growing your family or caring for your loved ones, you have our full support. Enhanced leave options include 26 weeks of paid leave for birthing parents and 18 weeks of paid leave for non-birthing parents.
Community and personal development
At Waymo, you'll find a range of opportunities to grow, connect, and give back. We offer education reimbursement, personal and professional development, mentorship, and other ways to connect through Employee Resource Groups (ERGs), other internal groups, and even time off to volunteer.
Cool perks
Access to Google offices, cafes, wellness centers, massages, and so much more. To support your wellbeing at home, you can enjoy at-home fitness and cooking classes, and more.
To ensure thorough consideration of each application, candidates may submit up to 5 job applications within a 60-day period. We encourage you to carefully review job descriptions and apply to positions that best match your skills. Applications beyond this limit will not be considered.
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