Software Engineer II, TPU Compiler
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 1 year of experience with data structures or algorithms.
- Experience with C++, compiler construction and performance optimization.
Preferred qualifications:
- Master's degree in Computer Science or a related technical field.
- Experience with Machine Learning architecture and infrastructure.
- Understanding of accelerators,, for example, VLIW, Vector machines, GPUs or DSPs.
- Understanding of debugging correctness and performance issues at all levels of the stack.
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.
The TPU Backend and NPI team is at the crux of Machine learning, Compilers and TPU hardware. We collaborate with teams across hardware and software, and enable Google to have the industry's most performant machine learning chip (TPU) at the hands of machine learning (ML) modeling teams. The vast majority of all machine learning at Google flows through tools that the TPU backend and NPI team is creating, so impact is both immediate and massive. Enable a novel processor to accelerate machine learning workloads. This hardware will be deployed at scale and will power some of Google's most critical production workloads. Opportunities include performance optimization, programmability, usability and co-design of next generation hardware.
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 force 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.
Responsibilities
- Write product or system development code. Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
- Contribute to the TPU compiler for a novel processor designed to accelerate machine learning workloads. Target and compile high-performance implementations of operations at a distributed scale.
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