Description

Minimum qualifications:

• Bachelor's degree, or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.
• Experience developing software applications using the C programming language.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
• 3 years of experience working in a complex, matrixed organization.
  
• Experience with Nvidia Collective Communications Library (NCCL), Nvidia Index Library (NIXL), Deep Learning Execution Provider (DeepEP), and Mooncake.

About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

Network Infrastructure Team's mission is to be an expert in the hardware-software interface, and to influence the co-design of Google software and hardware to strike the right balance between performance-optimized hardware and the implications of the API design on software performance and maintainability.

In this role, you will work with hardware designers, vendors, and Google software teams alike, you will think about the software and hardware performance, and how API design affects these. You will work on specific offload technologies, including AI Training and Inference Transport Layers as well as dataplane encryption.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud's Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

The US base salary range for this full-time position is $207,000-$300,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Set and communicate team priorities that support the broader organization's goals.
• Manage and lead the team that is developing the next generation Artificial Intelligence (AI) and Machine Learning (ML) Networking solutions as well as Smart Network Interface Cards (NICs) at Google, taking the projects through development into production.
• Enable the team to advance new approaches to leverage offloads efficiently with Google hardware and software.
• Guide the team to build and test software in C for use on Google's Machine Learning (ML) Library solutions and Smart Network Interface Cards (NICs).
• Align strategy, processes, and decision-making across teams.

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Requisition #: 108704223129936582

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