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, debugging & evaluation, optimization, deployment, and monitoring. These efforts have resulted in making machine learning more accessible to teams at Waymo, including Perception, Planner, Research and Simulation, 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 are looking for a Senior engineer with model optimization expertise to help us improve compute performance on our car. In this hybrid role, you will report to our Head of Model Optimization.

You will:

• Work across the entire ML framework/compiler stack (e.g. JAX, XLA, Triton, and CUDA), and system-efficient deep learning models.
• Deep dive into the whole stack of ML software stack, from custom ops, framework/ ML compiler, to low-level libraries.
• Apply model optimization and efficient deep learning techniques to models and optimized ML operator libraries.

You have:

• M.S. in CS, EE, Deep Learning or a related field
• 3+ years of experience on model optimization or efficient deep learning techniques
• Strong Python or C++ programming skills
• Solid experience with designing, training and debugging deep learning models to achieve the highest scores/accuracies.

We prefer:

• PhD in CS, EE, Deep Learning or a related field.
• Deep knowledge on system performance, GPU optimization or ML compiler.
• 5+ years of experience on model optimization or efficient deep learning techniques

#LI-Hybrid