Minimum qualifications:

• Bachelor's degree in Computer Science, related technical field, or equivalent practical experience.
  
• 8 years of experience in software development, and with data structures/algorithms in one or more programming languages (e.g., Python, C, C++).
  
• 5 years of experience in a technical leadership role; overseeing projects, with 5 years of experience in a people management, supervision/team leadership role.
• Experience delivering high performance systems to support research to production efforts.
  

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a technical related field.
  
• 5 years of experience working in a complex, matrixed organization.
• 5 years of experience with machine learning algorithms and tools (e.g. TensorFlow), or applied ML (e.g., deep learning, natural language processing).
  
• Experience with distributed computing or HPC.
  
• Experience with ML compilers or frameworks (not necessarily involving TPUs).
  

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.

The AI @ Scale team is part of our Core ML organization, which rolls into Cloud. We tasked with enabling models at unprecedented scale and performance for Google DeepMind, Gemini, Ads, and Cloud while shortening the distance between research and production. We’re hiring a Senior Engineering Manager who will help us scale and accelerate training and serving for large GenAI models on a variety of accelerator hardware such as GPUs and several generations of TPUs. Additionally, the team supports ongoing research in scaling models further which require (re)inventing new approaches, unparalleled in the industry.

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.

The US base salary range for this full-time position is $237,000-$337,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. 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

• Lead and mentor the team responsible for a portfolio of ML compilation projects. Set and communicate priorities that support the broader organization’s goals.
  
• Oversee large-scale system design that supports research to production efforts.
  
• Own existing projects on the team’s roadmap, but also develop our long-term technical vision and roadmap to help drive innovative projects forward.
  
• Partner with technical leads for AI @ Scale, as well as GPU and TPU compiler teams, to ensure that the team’s projects fit into the wider ML compilers ecosystem. Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
  
• Collaborate closely with various cross-functional product areas across Google and Google DeepMind.