Machine Learning Engineer, Runtime Optimization

Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.

The ML Platform team at Waymo provides a set of tools to support and automate the lifecycle of the machine learning workflow, including feature and experiment management, model development, optimization and monitoring. These efforts have resulted in making machine learning more accessible to teams at Waymo, including Perception, Planner, Research and Simulation.

We are looking for engineers with ML software & systems expertise to help us improve compute performance on both cloud and car. You'll work across the entire ML stack from the system perspective, from efficient deep learning models, model compression, ML software (e.g. JAX, XLA, Triton, and CUDA), to . You will be pleasantly challenged with deploying Waymo ML models on limited computation resources. In this hybrid role, you will report to the Senior Manager of Runtime and Optimization.

In this role you will:

• Collaborate with  the world-class Waymo ML practitioners in perception, planner, research and simulation to analyze ML workload performance and apply optimization techniques.
• Assist in the development and implementation of efficient deep learning solutions.
• Support the building of tools for benchmarking and optimizing deep learning models
• Contribute to the analysis of ML software stack and model performance.
• Develop an efficient ML runtime system and optimized ML operator libraries for the diverse hardware options on Waymo’s platforms.

You have: 

• B.S. in CS, EE, Deep Learning or a related field
• 2+ years of industry experience
• Strong C++ programming skills
• Experience in developing on or using deep learning frameworks (e.g., PyTorch, TensorFlow, JAX, etc.)
• Passion for developing and optimizing ML software stacks for modern ML accelerator architectures (framework, runtime library, ML compiler, efficient deep learning  etc.)

We Prefer:

• M.S. or PhD in CS, EE, Deep Learning or a related field.
• Strong Python programming skills.
• Experience on system performance, GPU optimization or ML compiler.
• Experience on ML frameworks, ML compiler and IRs (MLIR, HLO, Triton) or modern ML system architectures.
• Experience on heterogeneous runtime systems and ML inference/serving engine.

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.