Software Engineer, ML Compilers, Silicon

Minimum qualifications:

• Bachelor's degree in Electrical/Electronics Engineering, Computer Engineering, Computer Science, or equivalent practical experience
• 2 years of development experience in C++
• Experience in data structures and algorithms

Preferred qualifications:

• Master's degree or PhD in Electrical/Electronics Engineering, Computer Engineering, Computer Science, or a related field
• Experience with compilers
• Experience in power and performance optimizations
• Understanding of hardware, especially hardware that provides a high degree of parallelism

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 team that builds Google Tensor - Google’s custom System-on-Chip (SoC) that powers the latest Pixel phones. Tensor makes transformative user experiences possible with the help of cutting-edge Machine Learning (ML) running on Tensor TPU. Our team’s work enables Gemini Nano, our efficient AI model for on-device tasks to run on Pixel phones. Our goal is to productize the latest ML innovations and research by delivering computing hardware and software.vAs a Software Engineer you will work on developing ML compilers for the Tensor TPU to accelerate Generative AI and other complex machine learning models running on custom hardware accelerators. Along with your technical expertise, you will manage project priorities, deadlines, and deliverables.

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.

• Build compilers and tools that efficiently map ML models (with a particular focus on always-on computing use cases) to the hardware ISA.
• Evaluate various trade-offs of different parallelization strategies such as performance, power, energy and memory consumption.
• Collaborate with machine learning researchers to constantly improve the domain-specific compiler.
• Collaborate with hardware engineers to evolve future accelerators.