Senior Machine Learning Engineer, Runtime & Optimization
Waymo is an autonomous driving technology company with a mission to make it safe and easy for people and things to get where they’re going. Since our start as the Google Self-Driving Car Project in 2009, Waymo has been focused on building the Waymo Driver—The World’s Most Experienced Driver™—to improve everyone's access to mobility while saving thousands of lives now lost to traffic crashes. Our Waymo Driver powers Waymo One, our fully autonomous ride-hailing service, as well as Waymo Via, our trucking and local delivery service. To date, Waymo has driven over 20 million miles autonomously on public roads across 25 U.S. cities and conducted over 20 billion miles of simulation testing.
At Waymo, we are mission-driven and believe deeply in the opportunity of autonomous driving technology to improve mobility and make people's lives better. We are united by purpose and responsibility (for our employees and riders alike). We are looking for kind, committed, employees who have integrity, dream big, work together as one team and create a sense of belonging for one another that is the foundation of our culture. We want each team member to feel welcomed and included in every step of our exciting journey.
The ML Platform team at Waymo provides a set of tools and technologies to support and automate the lifecycle of the machine learning workflow, including feature and experiment management, model development, debugging & evaluation, optimization, deployment, and monitoring. These efforts have resulted in making machine learning more accessible to teams at Waymo, including Perception, Behavior Prediction, Planner, Maps and Research, ensuring greater degrees of consistency and repeatability, and addressing the “last mile” of getting models into production and managing them once they are in place. We work hand in hand with machine learning experts in all parts of the company as well as our collaborators across Alphabet.
We are looking for engineers with ML software or ML systems expertise to help us improve compute performance on our car. You’ll work across the entire ML framework/compiler stack (e.g. JAX, XLA, Triton, and CUDA), as well as system-efficient deep learning models. You will be pleasantly challenged with deploying a hugely diverse set of Waymo ML models on limited computation resources. Non-exhaustive examples of the types of work you will work on:
- Collaborate with ML practitioners on models for perception, behavior prediction and planner, to understand their models and modify model architectures to run faster on the car.
- Deep dive into the whole stack of ML software stack, from custom ops, framework/ ML compiler, to low level libraries. Analyze numeric behaviors. Make sure inference results are stable and consistent across multi-devices. Develop tools/system software for optimal resource usage, hardware efficiency, and platform reliability in a ML serving system.
- Analyze the ML workload performance; Apply model optimization and efficient deep learning techniques to models; Develop highly optimized ML operator libraries.
- Build tools to benchmark, optimize and productize deep learning models for a streamlined and robust onboard and offboard deployment.
At a minimum, we’d like you to have:
- B.Sc in Computer Science, Mathematics or a related field
- 3+ years of industry experience
- Strong C++ programming skills
- Experience in developing on or using deep learning frameworks (e.g., PyTorch, TensorFlow, ONNX, etc.)
- Passion for developing and optimizing ML software stacks for modern ML accelerator architectures (framework, runtime library, ML compiler, efficient deep learning etc.)
- Working knowledge on system performance, GPU optimization or ML compiler
It’s preferred if you have one of the following:
- M.Sc or PhD in Computer Science, Mathematics or a related field.
- Strong Python programming skills.
- Strong experience with efficient deep learning and/or model optimization techniques such as quantization, NAS, distillation.
- Solid experience with designing, training and debugging deep learning models to achieve the highest scores/accuracies.
- In-depth knowledge of ML frameworks, ML compiler and IRs (Triton, HLO, MLIR, Relay) or modern ML system architectures.
While at Waymo, you will enjoy benefits that cover…
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, a Flexible Spending Account (FSA), a Health Saving Account (HSA), and special wellness programs.
Financial wellness: Your financial peace of mind is important to us. At Waymo, we offer competitive compensation, bonus opportunities, equity, a generous 401(k) plan, 1-on-1 financial coaching, a 529 College Savings Plan 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 paid parental leave (birthing parent gets 24 weeks of paid leave with up to 4 weeks of additional leave before their due date, and non-birthing parent gets 18 weeks of paid leave), and 20 days of subsidized backup childcare or adult/elder care.. Access to fertility care or adoption support as you grow your family.
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.
#LI-Hybrid
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.