Software Engineer III, Core ML Performance
Software Engineer III, Core ML Performance
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages.
- 2 years of experience with performance, large-scale systems data analysis, visualization tools, or debugging.
- 2 years of experience with computer architecture, performance analysis, and performance modeling.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures or algorithms.
- Experience developing accessible technologies.
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.
We are the Core ML Frameworks team, responsible for large parts of Google's production ML stack. We collaborate closely with Google DeepMind and other teams across Alphabet to build solutions that power the future of AI, both within the company and across the industry via GCP. Join Core ML and make a significant impact on Alphabet's vast ML infrastructure, addressing technical challenges that directly impact the performance, efficiency and scalability of AI across Google.
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.Responsibilities
- Contribute to the development and maintenance of Tokamax, a unified open-source kernel library, creating a home for high-quality, well-tested, easy-to-use, and performant kernels available to both internal and external users.
- Build infrastructure and tooling for kernel development, including bench-marking suites, auto-tuning frameworks, performance analysis tools, debugging tools, and continuous integration pipelines to ensure the correctness and performance of custom kernels across different hardware and model configurations.
- Design, develop, and optimize high-performance custom kernels (using languages like Pallas, Mosaic, and Triton) aiming TPU and GPU architectures for key machine learning operations.
- Investigate and implement custom kernel support for new accelerator hardware generations/features and emerging ML operations.
- Contribute to the documentation and usability of kernel libraries tools and libraries to lower the barrier to entry for researchers and engineers looking to write or leverage custom kernels.
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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.
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