Staff Software Engineer, Machine Learning Performance

Waymo's Compute Team is tasked with a critical and exciting mission: We deliver the compute platform responsible for running the fully autonomous vehicle’s software stack. To achieve our mission, we architect and create high-performance custom silicon; we develop system-level compute architectures that push the boundaries of performance, power, and latency; and we collaborate closely with many other teammates to ensure we design and optimize hardware and software for maximum performance. We are a multidisciplinary team seeking curious and talented teammates to work on one of the world’s highest performance automotive compute platforms.

This role follows a hybrid work schedule, and you will report to the Tech Lead Manager of the Machine Learning Performance team.

You will:

• Act as Technical Lead (TL) for a small team (~5 engineers) focusing on individual ML model performance optimization and delivering maintainable, high-quality solutions.
• Set the technical vision, direction, and multi-quarter roadmap for ML performance optimization within the team's scope
• Drive and coordinate large, open-ended technical projects that span multiple application and infrastructure teams, ensuring timely and robust delivery
• Collect, trace, and analyze application/ML model performance for complex optimization opportunities, and prototype/generalize solutions at the application, compiler, or infrastructure level (firmware, runtime, framework)
• Influence and motivate infrastructure teams (e.g., compiler) to prioritize and land performance-critical optimizations, setting clear expectations using solid methodology (e.g., roofline)
• Provide technical mentorship and guidance to team members, helping them to grow and ensuring technical excellence and code health across the team's deliverables

You have:

• MS degree in Computer Science/Electrical Engineering or equivalent, or equivalent practical experience
• 5+ years of experience writing complex C++ code
• 5+ years of experience writing code in Python
• 7+ years experience in optimizing compute performance for ML applications
• Experience in compute architectures, performance analysis, and optimization methodologies
• Communicate well to cross-functional teams and effectively mitigate timezone differences

We prefer:

• Experience in ML modeling and also ML compiler implementation
• Experience in performance tools, simulators, and HW/SW codesign
• Proficiency in building and nurturing effective collaborations across application teams and infrastructure teams
• Experience with pruning, quantization, and other model performance optimization techniques