Software Engineer, Hardware Accelerators Performance, GeminiApp, DeepMind
United StatesJob$147–210K/yrPosted 1 day agoStill listed today
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Job overview
DeepMind seeks a Software Engineer to improve Gemini model performance on TPUs and GPUs, profiling large workloads, designing custom kernels, building benchmarking pipelines, and influencing accelerator architectures, collaborating with ML and neuroscience researchers.
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Full job description
Software Engineer, Hardware Accelerators Performance, GeminiApp, DeepMind Share Software Engineer, Hardware Accelerators Performance, GeminiApp, DeepMind
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corporate_fareDeepMindplaceMountain View, CA, USA; San Francisco, CA, USA
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info_outline XApplicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; San Francisco, CA, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in C++ or Python.
- Experience with profiling tools (e.g., gProf, Valgrind, or VTune) for performance optimization.
- Experience in software development for hardware accelerators (e.g., CPUs, GPUs, or TPUs), including memory-hierarchy or instruction-level tuning.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 3 years of experience with advanced data structures, algorithms, and machine learning optimization.
- Experience developing accessible technologies.
About the job At Google DeepMind our mission is to build the world's first general-purpose learning agent. Central to this mission is the complex task of measuring the intelligence of our prototypes. As a Software Engineer, you will be working with the cutting edge AI agents developed by our exceptional team of Machine Learning and Neuroscience research scientists. Your responsibilities will include everything from creating systems for agent testing using 2D and 3D games to developing test problems within physics simulators. You will create graphical visualization of results, build competitive agent leaderboards and test new algorithms on robots. To succeed in this role you will need to have a strong foundation in software engineering and enjoy working on a wide range of challenging problems within a mission-driven team. Our mission is to maximize the performance and scaling of hardware accelerators (TPUs and GPUs) across Google DeepMind and Google, with a core focus on Gemini model training and serving. We work across the JAX stack—spanning custom kernel development, large-scale model sharding, performance analysis, and compiler optimizations. Operating at the intersection of modeling, compilers, and infrastructure, we collaborate closely with partner teams to deliver end-to-end efficiency. Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google. Responsibilities
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Improve the training and serving efficiency of Gemini models on hardware accelerators (TPUs and GPUs), spanning model configurations, execution runtimes, and dedicated compiler passes.
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Profile large-scale distributed workloads to diagnose compute, memory, and communication bottlenecks, identifying high-impact optimization opportunities.
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Design and implement high-performance, low-level custom kernels for critical model operators to unlock peak hardware utilization.
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Build and maintain automated benchmarking pipelines and diagnostic tooling to track, reproduce, and guard against performance regressions.
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Influence next-generation accelerator architectures and compiler roadmaps by feeding back empirical workload profiles and model requirements.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate 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 also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire. If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form. 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. Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.
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