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GPU Performance Engineer

_corporate_fare_ Google _place_ Sunnyvale, CA, USA

Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

Minimum qualifications:

+ 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.

Preferred qualifications:

+ 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.).

+ Knowledge of low-level GPU programming (CUDA, Triton, CUTLASS, etc.) and performance engineering techniques.

+ Understanding of modern GPU architectures (NVIDIA, AMD, or other AI accelerators), memory hierarchies and performance bottlenecks.

+ Understanding of modern Large Language Models (LLMs) and their deployment on AI accelerators.

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.

Graphics Processing Unit (GPU) Performance team is responsible for optimizing, modeling and evaluating GPU systems for comparative analysis and benchmarking of Google’s ML (used internally and by external Google Cloud customers) workloads/hardware. This team strives for extracting maximum efficiency in Google’s GPU fleet.

In this role, you will evaluate current and future ML workloads/hardware using detailed benchmarking and simulation of ML systems and guide decision making for the Cloud hardware teams and cross-functional optimization efforts to improve GPU fleet efficiency.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

The US base salary range for this full-time position is $141,000-$202,000 + 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 aboutbenefits at Google (https://careers.google.com/benefits/) .

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 (CUTLASS, 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 strategic deployment of Google’s GPU fleet by working with various product teams across Google.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

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 alsoGoogle's EEO Policy (https://www.google.com/about/careers/applications/eeo/) ,Know your rights: workplace discrimination is illegal (https://careers.google.com/jobs/dist/legal/EEOC\_KnowYourRights\_10\_20.pdf) ,Belonging at Google (https://about.google/belonging/) , andHow we hire (https://careers.google.com/how-we-hire/) .

If you have a need that requires accommodation, please let us know by completing ourAccommodations for Applicants form (https://goo.gl/forms/aBt6Pu71i1kzpLHe2) .

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. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCP_EEO_Post.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.