Technical Lead, Google Cloud TPU

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 8 years of experience in software development, focusing on building distributed cloud services.
• 5 years of experience in a formal engineering technical leadership role, leading software engineering teams.
  
• 2 years of experience in LLM training or inference, including performance optimizations, distributed execution, GPU or TPU acceleration, or PyTorch, JAX, or TensorFlow programming.
• Experience integrating generative AI tools or LLM interfaces into workflows.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.

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.

This role is a unique leadership opportunity to technically lead by example an engineering team dedicated to critical Google Cloud Tensor Processing Unit (TPU) software services, which empower Google’s global AI customers. As a Technical Lead (TL), you will lead the architecture and execution of large-scale ML infrastructure, requiring a deep understanding of Large Language Model (LLM) operations from chip level to fleet levels. You will be responsible for solving complex ML infrastructure issues, driving technical strategy, fostering a high-performance team culture, and working directly with customers to ensure successful landings.

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

• Act as the crucial bridge between raw Tensor Processing Unit (TPU) silicon and production-ready machine learning, owning the software integration and operational ecosystem that powers Google's most advanced AI.
• Lead the end-to-end New Product Introduction process—coordinating complex cross-functional launches from initial concept to General Availability—while ensuring the reliability and scalability of a massive fleet of TPU chips.
• Drive foundational engineering efforts, such as developing the TPU runtime API, qualifying the OS images for TPU Virtual Machines (VMs) and Bare Metal instances, and managing fleet-wide reliability through advanced telemetry and automated repair workflows.
• Lead the architecture, technology and the overseeing of implementation of the TPU solutions to production.
• Analyze customers’ issues (working with customers and the field team) and translate these into viable technical solutions.