Staff Software Engineer/Tech Lead, ML Network Infrastructure

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.

As a Staff Engineer on the ML Network Infrastructure team, you'll set the technical strategy for Google's next-generation ML network fabrics. You will architect and build software for distributed services, abstractions, and the components of the system that operates and powers Google’s ML network infrastructure. You will be passionate about networking, control-plane software, and distributed systems, and enjoy working with both software and hardware across the full stack.

The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Lead the technical strategy and architecture of next-generation control planes and software infrastructure for highly-available ML network fabrics.
• Design and implement agentic SDLC, leveraging LLMs and automated workflows to streamline development aspects like triaging and testing.
• Drive all aspects of development—from requirements definition to global deployment—upholding reliability standards for distributed networking systems.
• Collaborate and drive architectural alignment across Networking Infrastructure and Cloud with senior engineers and product managers.
• Mentor individual engineers, aligning long-term career goals with project priorities and business objectives.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 8 years of experience programming in C++.
• 5 years of experience testing, and launching software products.
  
• 5 years of experience building and developing large-scale infrastructure, distributed systems or networks.
• 3 years of experience with software design and architecture.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 8 years of experience with data structures and algorithms.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
• Experience with Data Center Networking, Software Defined Networking (SDN) architectures, and high-performance RPC frameworks.