Senior Software Engineer, Training, ML Infrastructure

The Waymo ML Infrastructure team works with Research and Production teams to develop models in Perception and Planning that are core to our autonomous driving software. We help our partners by offering the best solutions for the entire model development lifecycle. These solutions are developed in close collaboration with teams at Google. They are geared towards both scaling models and solving problems unique to ML for autonomous driving. 

We build a set of libraries and tools that enhance TensorFlow and JAX, and address scalability, reliability, and performance challenges faced by Waymo’s ML practitioners: training fast and at scale, increasing ML accelerator efficiency, fine-tuning multimodal LLMs for autonomous driving tasks, discovering hyper-parameters, re-training neural networks, computing reliable and noiseless metrics on validation sets, and validating newly trained DNNs when deployed into the full onboard software stack. 

In this role, you'll:

• Report into the Head of ML Training
• Design distributed systems tailored for machine learning workloads of different sizes, considering factors such as scalability, fault tolerance, and resource use
• Optimize system performance by identifying bottlenecks and implementing efficient algorithms for distributed training
• Increase training efficiency of different neural network architectures
• Improve the developer experience and performance of our scalable ML framework
• Collaborate with machine learning engineers and other partners to understand their requirements and provide infrastructure support for their experiments and projects.

At a minimum we'd like you to have:

• BS in Computer Science, Math, or 5+ years equivalent real-world experience
• Python or C++ industry experience
• Prior experience with Machine Learning frameworks (e.g., TensorFlow, PyTorch) and distributed training algorithms
• Practical familiarity using ML accelerator profiling tools to uncover performance bottlenecks
• Understand ML compiler infrastructure, such as of HLO and MLIR 
• Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and experience deploying and managing distributed systems in cloud environments

It's preferred if you have:

• MS in Computer Science, Math
• Prior work scaling model training to multiple accelerators
• Prior experience on ML compiler optimization such as TVM or XLA
• Knowledge of optimization and deep learning algorithms

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