Description

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 2 years of experience working with embedded systems or device software.
• 2 years of experience with compilers (development, parallelization, etc.).
• 2 years of experience with software development in one or more programming languages (e.g. C ), or 1 year of experience with an advanced degree.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical fields.
• Experience in optimizing ML models for inference.
• Experience developing compilers within the context of accelerator-based architectures.
• Experience in MLIR or LLVM.

About the jobGoogle'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 manage information at a 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.

As a part of this team, you will contribute to building Google Tensor TPU , Google's custom System-on-Chip (SoC) ML accelerator that powers the latest Pixel phones. As a part of this team, you will help make transformative user experiences possible by leveraging cutting-edge Machine Learning (ML) running on Tensor TPU. You will be responsible for analysis, optimization, and compilation of ML models targeting the EdgeTPU. You will enable Gemini Nano, our efficient AI model for on-device tasks to run on Pixel phones and leverage the latest ML innovations and research by delivering computing hardware and software.Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.

The US base salary range for this full-time position is $147,000-$211,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Analyze and improve compiler quality, performance, optimization decisions, correctness and compilation time as part of the EdgeTPU compiler team.
• Develop and enhance parallelization and scheduling algorithms to reduce compute and data movement costs for executing ML workloads on the EdgeTPU.
• Collaborate with EdgeTPU architects to shape future accelerators, the Hardware/Software (HW/SW) interface, and co-optimizations of the next-generation EdgeTPU architectures.
• Work on efficient mapping of generative AI models and other key workloads into EdgeTPU instructions through the compiler.

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Requisition #: 123315190769820358

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