Senior Software Engineer, ML Compilers, TPU, YouTube

Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience programming in C++ or Python. 5 years of experience testing, and launching software products. 3 years of experience with software design and architecture. Experience with state-of-the-art ML compilers and their internals, experience writing compiler optimization passes. Experience with ML frameworks such as TensorFlow, JAX, and PyTorch, or ML compilers (e.g., accelerated linear algebra (XLA)) Preferred qualifications: Master's degree or PhD in computer science or related technical fields. Experience developing accessible technologies. Experience with debugging correctness and performance issues at all levels of the ML software stack. Familiarity with accelerator HW architectures (TPUs/GPUs). 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. With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. On this team, you will own the optimization of the models powering the YouTube algorithm. Your work will range from contributing to the Accelerated Linear Algebra (XLA) compiler for Google's custom Tensor Processing Units, to authoring custom Pallas kernels in JAX, maximizing fleet utilization and the value delivered to users. You will build support and optimize new and existing models in our RecSys stack, including new model architectures while adapting to next-generation TPU hardware. You will engage in state-of-the-art model and TPU compiler co-design, with opportunities to work up and down the stack ranging from end-user ML models down to Hardware/Software architecture. At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $174000 - $253000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities Contribute to the compiler for a novel processor designed to accelerate machine learning workloads. Target and compile high-performance implementations of operations at distributed scale. Design and implement new compiler passes that extract more performance out of current and next-generation TPUs for our unique LEM (Large Embedding Models) requirements, directly impacting fleet efficiency. Collaborate closely with YouTube’s Next Platform Evaluation team and Google’s hardware designers to co-design future processors.