GPU Performance Engineer

Google • Sunnyvale, CA

5h • $141,000 - $202,000

About The Position

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. GPU Performance team is responsible for optimizing, modeling and evaluating GPU systems for comparative analysis and benchmarking for Google’s internal Machine Learning (ML) workloads. We strive for extracting maximum efficiency in Google’s growing GPU fleet. The team identifies performance opportunities in Google production and research ML workloads and lands improvements that impact the entire fleet. The team also evaluates current and future ML workloads through simulations and comparative benchmarks to guide decision making for the Cloud hardware teams. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Requirements

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• Experience in low-level GPU programming (e.g., CUDA, Triton, CUTLASS, etc.) and performance engineering techniques.
• Experience in modern GPU architectures (NVIDIA, AMD, or other AI accelerators), memory hierarchies, and performance bottlenecks.

Nice To Haves

• Master's degree or PhD degree in Computer Science or related technical fields.
• 2 years of experience with data structures or algorithms in either an academic or industry setting.
• Experience with compiler improvement, code generation and runtime systems for GPU architectures (OpenXLA, MLIR, Triton, etc.).
• Understanding of modern Large Language Models (LLMs) and their deployment on AI accelerators.

Responsibilities

• Build improvements for the latest generation of Graphics Processing Unit (GPUs) that power Google’s most critical products and services, impacting billions of users worldwide.
• Identify performance bottlenecks and drive improvements across the breadth and depth of Google’s GPU software stack from ML compiler cost model design (OpenXLA, Triton, MLIR) to optimizing performance GPU kernels (Pallas Mosaic, CuTe) to cross node model serving configurations (e.g., disaggregated serving, paged attention).
• Influence the technical direction of the GPU software ecosystem at Google by collaborating with Modeling, XLA:GPU, Deepmind and Performance Tooling teams.
• Influence the deployment of Google’s GPU fleet by working with various product teams across Google.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees