Senior Software Engineer, GPU Performance

Senior Software Engineer, GPU Performance Apply X Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; New York, NY, USA . Bachelor’s degree or equivalent practical experience. 5 years of experience with software development in one or more programming languages. 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture. Experience with modern GPU architectures (NVIDIA, AMD, or other AI accelerators), memory hierarchies, and performance bottlenecks. Experience low-level GPU programming (CUDA, Triton, CUTLASS, etc.) and performance engineering techniques. Experience with modern LLMs and their deployment on AI accelerators. Preferred qualifications: Master's degree or PhD in Computer Science or related technical field. 5 years of experience with data structures and algorithms. 1 year of experience in a technical leadership role. Experience with compiler optimization, code generation, and runtime systems for GPU architectures (OpenXLA, MLIR, Triton, etc.). About the job 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. While known for pioneering work with TPUs, GPUs are an equally vital and rapidly expanding frontier within Google's machine learning infrastructure. GPUs are indispensable to Google’s ever-evolving landscape for strategic, pragmatic, and performance-driven reasons — ensuring top performance for our ML models, adapting to ML workloads, achieving results, and influencing next-gen GPU architectures via strategic partnerships. In recognition of hardware as a strength, Google’s Core ML organization is heavily invested in growing a powerhouse team of GPU experts, and we invite you to be at its vanguard. This is your opportunity to move beyond incremental improvements and architect truly transformative solutions, shaping the future of AI and accelerated computing for Google and the world. The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We're the driving channel behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more. The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google . Responsibilities Build optimizations for the latest generation of GPUs that power Google’s most critical products and services, impacting billions of users worldwide. Address the most challenging performance bottlenecks through Google’s unparalleled access to the latest generation of GPUs, tooling, and a decade of experience building AI accelerators. Drive optimizations across Google’s GPU software stack from ML compiler cost model design to optimizing high performance GPU kernels to cross node model serving configurations. Influence the technical direction of the GPU software ecosystem at Google by collaborating with ML, compiler design, and systems architecture. Influence the deployment of Google’s GPU fleet by working with various product teams across Google. Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire . Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting. To all recruitment agencies: Google does not accept agency resumes. 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