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Software Engineering Manager, AI/ML Infrastructure and Performance Engineering

Google · Bangalore

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Collected role description

Role overview

Software Engineering Manager, AI/ML Infrastructure and Performance Engineering at Google

Required qualifications

  • Minimum qualification: Bachelor's degree or equivalent practical experience.; 8 years of experience with software engineering, machine learning infrastructure, computer architecture, distributed computing, people management, debugging tools, communication.; Experience with people management, and building infrastructure to improve performance of Machine Learning (ML) systems and applications.

Preferred qualifications and skills

  • Preferred qualification: Experience with Performance Optimization, Graphics Processing Unit (GPU) Programming, High Performance Computing, Large Language Model, Open Source Contributor.; Experience with the Machine Learning infra and frameworks and hands-on experience with GPU or Tensor Processing Unit (TPU) performance analysis.; Experience in building agentic workflows for performance debugging and optimization. Ability to generate ideas and resolve ambiguity.; Hands-on experience with Machine Learning (ML) frameworks such as TensorFlow, JAX, and PyTorch, Keras. Experience with ML Inference frameworks such as vLLM, SG Lang, Pathways and experience in open-source software development, including experience in releasing and supporting open-source projects.

Employment details

  • Location: Bengaluru [Karnataka] [India]

Application details

  • Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy .

About the employer

  • Google is proud to be an equal opportunity and affirmative action employer.
  • 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.
  • Please do not forward resumes to our jobs alias, Google employees, or any other organization location.

Additional role details

  • 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 .
  • If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
  • To all recruitment agencies: Google does not accept agency resumes.
  • Google is not responsible for any fees related to unsolicited resumes.
  • 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.

Collected minimum qualification

Bachelor's degree or equivalent practical experience.; 8 years of experience with software engineering, machine learning infrastructure, computer architecture, distributed computing, people management, debugging tools, communication.; Experience with people management, and building infrastructure to improve performance of Machine Learning (ML) systems and applications.

Collected preferred qualification

Experience with Performance Optimization, Graphics Processing Unit (GPU) Programming, High Performance Computing, Large Language Model, Open Source Contributor.; Experience with the Machine Learning infra and frameworks and hands-on experience with GPU or Tensor Processing Unit (TPU) performance analysis.; Experience in building agentic workflows for performance debugging and optimization. Ability to generate ideas and resolve ambiguity.; Hands-on experience with Machine Learning (ML) frameworks such as TensorFlow, JAX, and PyTorch, Keras. Experience with ML Inference frameworks such as vLLM, SG Lang, Pathways and experience in open-source software development, including experience in releasing and supporting open-source projects.

Collected experience requirement

8 years of experience with software engineering, machine learning infrastructure, computer architecture, distributed computing, people management, debugging tools, communication.