Tech Lead Manager, ML Accelerator Fleet Efficiency

Google Inc.; Sunnyvale (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google Sunnyvale seeks a Tech Lead Manager for the ML Accelerator Fleet Efficiency initiative. You will lead multiple teams, own ML infrastructure deployment at scale, and drive strategic decisions to maximize compute efficiency while preserving developer velocity.

You will mentor engineers, align roadmaps with product goals, and collaborate with cross-functional partners across Google Cloud to deliver impact.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience with one or more of the following: Speech/audio, reinforcement learning, ML infrastructure, or related ML field.
• 5 years of experience leading ML design and optimizing ML infrastructure.
• 3 years of experience in a technical leadership role.
• 2 years of experience in people management or team leadership.

Responsibilities

• Drive technical strategy, roadmaps, and adoption for large-scale ML infrastructure development.
• Innovate next directions for infrastructure over a 12-month horizon in a rapidly changing tech landscape.
• Exercise sound engineering judgment to guide sustainable engineering choices for ML systems at scale.
• Seek opportunities to drive efficiencies in ML workloads using scaling and related techniques.
• Lead a team of ~10 engineers to develop solutions that drive ML workload efficiency.

Education

Bachelor’s degree or equivalent practical experience

Job description

Tech Lead Manager, ML Accelerator Fleet Efficiency

Share Tech Lead Manager, ML Accelerator Fleet Efficiency

• link Copy link

corporate_fare Google place Sunnyvale, CA, USA

Advanced

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders;deep expertise in domain.

Share Tech Lead Manager, ML Accelerator Fleet Efficiency

• link Copy link
• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.

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.
• Experience with ML development, modeling, optimization, and infrastructure.
• Experience with TPUs, TPU system design, and GPUs.
• Experience with low-level programming.
• Expertise in ML compilers and runtimes.

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.

Our team drives machine learning computational efficiency. We manage software to optimize the utilization of hundreds of thousands of Google Accelerator Units globally. We build the software abstraction layer between ML models and physical TPU/GPU hardware.

Our mission is to eliminate resource waste across Google’s accelerator fleet, maximizing the physical utility of compute clusters while maintaining peak developer velocity and seamless runtime execution. We strive to provide a cohesive, highly efficient, and transparent runtime environment that enables ML teams to focus entirely on modeling and research rather than physical infrastructure constraints.

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.

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.

Our team drives machine learning computational efficiency. We manage software to optimize the utilization of hundreds of thousands of Google Accelerator Units globally. We build the software abstraction layer between ML models and physical TPU/GPU hardware.

Our mission is to eliminate resource waste across Google’s accelerator fleet, maximizing the physical utility of compute clusters while maintaining peak developer velocity and seamless runtime execution. We strive to provide a cohesive, highly efficient, and transparent runtime environment that enables ML teams to focus entirely on modeling and research rather than physical infrastructure constraints.

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: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google .

• Drive technical strategy, roadmaps, and adoption for large-scale ML infrastructure development.
• Innovate next directions for infrastructure over a 12-month time horizon given a rapidly changing technology landscape.
• Exercise sound engineering judgment to guide sustainable engineering choices for ML systems at scale.
• Seek additional opportunities to drive efficiencies in ML workloads using scaling, idle suspend, and improving these capabilities with existing and novel technologies.
• Lead a team of ~10 engineers to develop solutions that drive the efficiency of ML workloads.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.