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.

In this role, you will work with Accelerated Linear Algebra (XLA) TPU parallelizing compiler used to partition, optimize, and run large-scale machine learning models across multiple TPU accelerators for internal (e.g., Google Deep Mind) and external customers. You will contribute to be a vital part of the Google Gemini software infrastructure.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

• Write product or system development code for the Tensor Processing Unit (TPU) compiler (in C++).

• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.

• Contribute to a compiler which scales-out machine learning models across accelerators like TPU/Graphics Processing Unit (GPU) at Google and Cloud.

• Conduct static and runtime performance analysis of important large-scale production models.

• Design and implement performance optimizations and critical features, which increase the velocity of important production teams.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.

• 2 years of experience with software development in one or more programming languages.

• 2 years of experience with computer architecture, performance analysis, and performance modeling.

• 2 years of experience with performance, large-scale systems data analysis, visualization tools, or debugging.

Preferred qualifications

• Master's degree or PhD in Computer Science or related technical fields.

• 2 years of experience with data structures and algorithms.

• Experience in compilers, parallel algorithms, parallel computing.

• Experience with formal methods, performance analysis, advanced algorithms.