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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Generative AI Accelerator Architect and Performance Architect - **Company:** Google LLC - **Location:** Mountain View, CA, United States - **Experience:** Expert - **Salary:** $192,000.0 - $278,000.0 - **Contract:** Permanent contract - **Skills:** Bioinformatics, C++ (Programming Language), Python (Programming Language), Machine Learning, Tensorflow, Systems Architecture, Pytorch, Large Language Models, Deep Learning, Generative AI, Information Technology, Power Analysis (Cryptography) - **Published:** October 14, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3445793410&tx=UT545THZ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain., * Bachelor's degree in Computer Science, Electrical Engineering or a related field, or equivalent practical experience. * 10 years of work or academic research experience in computer or chip architecture, performance, or compiler. * Experience with modern Generative AI model architectures (e.g., Large Language Models, Vision Transformers, Image Diffusion Models, etc.). * Experience with one or more general purpose programming languages (e.g., C, C++, or Python) and deep learning frameworks (e.g., TensorFlow, JAX, or PyTorch)., * Master's or PhD degree in Computer Science or Electrical Engineering. * Experience in compute IP (NPU/TPU, GPU) development, system PnP modeling and thermal/power analysis. * Experience with design space explorations and hardware/software co-design for machine learning. * Proven track record in driving medium to large scale projects and result delivery. * Excellent communication skills. ## Description * Drive forward-looking GenAI ML architecture exploration for Tensor mobile SoCs while collaborating with research teams, system architecture teams, and compiler engineers to optimize future workloads from both all perspectives across the tech stack including hardware, software, use case, network, and external components. * Work with researchers and Product Manager (PM) teams to define system architecture requirements for future Generative AI use cases. * Apply advanced research in architecture and process technology to get breakthrough power and performance improvements on Generative AI workloads. * Optimize performance of GenAI use cases by defining an optimal model scheduling on the TPU compute engines. 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