Engineering Manager, Machine Learning Compilers, Silicon Full-time

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience with software development in one or more programming languages (e.g., Python, C, C , Java, JavaScript).
• 8 years of experience in machine learning or artificial intelligence.
• 3 years of experience in a technical leadership role; overseeing projects, with 2 years of experience in a people management, supervision/team leadership role.

Preferred qualifications:

• Master’s degree or PhD in Computer Science or related technical field.
• Experience in Hardware/Software codesign.
• Experience with compiler development with accelerator-based architectures.
• Experience in optimizing ML models for inference, MLIR, or LLVM.

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.

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.

Responsibilities

• Work as part of the Edge TPU compiler team, including analyzing and improving the compiler quality and performance on optimization decisions, correctness, and compilation time.
• Work with Edge TPU architects to design future accelerators, the hardware/software interface, and co-optimizations of the next generation Edge TPU architectures.
• Develop parallelization and scheduling algorithms to optimize compute and data movement costs to execute ML workloads on the Edge TPU.
• Work on efficient mapping of generative AI models and other key workloads into Edge TPU instructions through the compiler.
• Collaborate with ML model developers, researchers, and Edge TPU hardware/software teams to accelerate the transition from research ideas to user experiences running on the Edge TPU.