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. Our team is delivering state-of-the-art performance on OSS models to showcase the capabilities TPUs, to both in industry competitions and to optimize these models so our public customers can leverage the optimization recipes in their own models. 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. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities • Write product or system development code. Manually optimize models, using state-of-the-art techniques (sharding, quantization, custom kernels). • Develop principles from manual optimizations which can be automated via agentic AI (e.g., compute, communication, scheduling, or quantization cost models). • Land identified principles and recipes to build scalable solutions, for example, by collaborating with the compiler team on cost modeling or by building agentic tooling for headroom analysis. • Create scalable solutions to serve the third-party customer base by improving out-of-the-box software performance and open-sourcing tooling to external customers. • Develop trend analysis to identify performance issues in yet-unseen models, solving performance problems before they occur. While maintaining model benchmarks to ensure tracking of performance wins. 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. • Experience experimenting with AI agents or LLM-powered agentic workflows. • Experience in systems engineering. Preferred qualifications: • Master's degree or PhD in Computer Science or related technical fields. • Experience with low-level accelerator programming (e.g., CUDA, Triton, Pallas) and performance tuning techniques. • Experience with machine learning, compiler optimization, code generation, and runtime systems for GPU architectures (OpenXLA, MLIR, Triton, etc). • Debugging experience to improve performance of single-mode or multi-mode (distributed) systems. • Expertise in tailoring algorithms and ML models to exploit ML accelerator architecture strengths and minimize weaknesses. • Deep understanding of modern ML accelerator architectures (Nvidia/AMD GPUs, TPUs, Trainium, Cerebras, etc.), memory hierarchies, and performance bottlenecks.