The Staff Software Engineer, ML Performance, GPU role at Google focuses on optimizing and evaluating GPU systems for machine learning workloads. The position is part of the Core ML's GPU Performance team, which is responsible for performance analysis and optimization across Google's infrastructure. Engineers in this role will work on critical projects that influence next-generation GPU architectures and improve the efficiency of ML models. This position requires a blend of technical expertise in software development and machine learning infrastructure.

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience with ML design and ML infrastructure.
• Experience with modern GPU architectures and performance bottlenecks.
• Experience with low-level GPU programming and performance engineering techniques.

• Identify and maintain LLM training and serving benchmarks to drive performance improvements.
• Partner with product teams to optimize and scale LLMs on GPU hardware.
• Conduct architecture-level simulations and performance benchmarking.
• Analyze fleet-wide performance metrics to identify bottlenecks.
• Research and implement model and data efficiency techniques to enhance workload performance.

• Employees at Google are often offered benefits like comprehensive health insurance, 401(k) matching, and flexible work arrangements, among other benefits.