ML Performance Engineer

Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you're a software engineer or researcher who's curious and passionate about Level 4 autonomous driving, we'd like to meet you.

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.

In this role, you'll:

• Collect application/ML model performance traces and analyze for performance optimization opportunities
• Land the optimizations to the application/ML model code base byEvaluating the correctness of the change (including retrain the ML model to evaluate accuracy)
• Ensure the change is net-positive for the current onboard performance
• Work with the application teams to adopt or apply the optimizations
• Add proper testing to ensure optimized performance is tracked and not regressed in the future
• Land the optimizations to the infrastructure byPrototype the performance optimizations and evaluate its effectiveness on applications/ML models
• Generalize the optimization at the infra level (compiler, firmware, runtime, framework, etc.) and project the potential impact to all applications (ML models) across board
• Motivate the infra teams to land the optimization to the specific level of the stack, set the performance expectation through solid methodology (e.g. roofline) and ensure the infrastructure team is aligned about the expectation
• Once the optimization is landed by the infra teams, close the loop by evaluating the overall performance impact and ensure it's landed in the expected way

At a minimum, we'd like you to have:

• BS degree in Computer Science/Electrical Engineering or equivalent, or equivalent practical experience
• 3+ years of experience writing complex C++ code
• 3+ years of experience writing code in Python
• 1+ years experience in optimizing compute performance for ML applications
• Experience in compute architectures and performance analysis optimization methodologies

It's preferred if you have:

• Experience in ML compiler design and implementation
• Experience in performance tools, simulators, HW/SW codesign
• Experience in robotic application development/optimizations
• Proficiency in collaboration with application teams and infrastructure teams

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