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Google Sunnyvale seeks a software engineer to bridge ML workloads with TPU hardware, focusing on performance analysis and optimization of distributed systems and compiler architectures. You will identify bottlenecks, model workloads, and propose architectural improvements with measurable impact.
Responsibilities include developing benchmarking strategies, driving hardware-software co-design for ML accelerators, and collaborating with cross-functional teams to deliver production-ready
The role involves bridging the gap between ML workloads and TPU hardware through performance analysis and optimization of distributed systems and compiler architectures. Responsibilities include developing benchmarking strategies and driving hardware-software co-design to optimize ML accelerator architectures for production models.
Requirements: Candidates need a Bachelor's degree and at least 2 years of experience in software development, performance analysis, and computer architecture. Preferred qualifications include a Master's or PhD in Computer Science and experience with data structures and algorithms.
Key Skills: Software Development, Performance Analysis, Computer Architecture, Performance Modeling, Data Structures, Algorithms, Distributed Systems, Compiler Architectures, XLA, Hardware-Software Co-design, Benchmarking, Workload Characterization, Simulator Tools, Hardware Cost-models, ML Infrastructure, Data Analysis