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Google

Senior Engineering Manager, Cloud ML Compute Services

Bangalore, India

Minimum qualifications:

  • Bachelor's degree in Computer Science, related technical field, or equivalent practical experience.
  • 17 years of experience in the software industry with 7 years of experience in leading teams.
  • Experience building, managing, and leading teams to cloud software systems landings.
  • Experience with machine learning systems (training and serving for computer vision, speech recognition, natural language processing, machine translation models).
  • Programming experience in C++, Python, PyTorch, JAX, Tensorflow.
Preferred qualifications:
  • Experience leading projects in the areas of Cloud based services.
  • Track record of successful collaboration with internal and external partners.

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  • Experience working with distributed and parallel systems, information retrieval, LLMs, GenAI, computer vision, natural language processing, etc.

  • 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.

    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.

    Responsibilities

    • Recruit Machine Learning Engineers(MLEs) focused on AI/ML and performance optimization. Focus on optimizing performance of ML models on Cloud TPUs and GPUs.
    • Provide mentorship and technical guidance to the team, including roadmap and vision for team deliverables and efficient execution. Help tune PyTorch and JAX models for performance on TPUs and GPUs, and design, develop, test, deploy, maintain, and improve software.
    • Collaborate with peers across Cloud ML Compute Services (CMCS) to contribute to strategic leadership and build collaborative relationships in key partners organizations within CMCS, Core ML, Research, GCE, GKE, etc.
    • Lead and guide the team to work with the broader CMCS ML team to enable cutting edge PyTorch and JAX models at scale for LLMs, computer vision (image recognition, object detection, image generation), machine translation, rankings, recommendations, speech recognition, etc.

    Client-provided location(s): Bengaluru, Karnataka, India; Hyderabad, Telangana, India
    Job ID: Google-121708679637410502
    Employment Type: Other

    Perks and Benefits

    • Health and Wellness

      • Health Insurance
      • Dental Insurance
      • Vision Insurance
      • Life Insurance
      • Short-Term Disability
      • Long-Term Disability
      • FSA
      • HSA
      • Fitness Subsidies
      • On-Site Gym
      • Mental Health Benefits
    • Parental Benefits

      • Birth Parent or Maternity Leave
      • Non-Birth Parent or Paternity Leave
      • Fertility Benefits
      • Adoption Assistance Program
      • Family Support Resources
      • Adoption Leave
    • Work Flexibility

      • Hybrid Work Opportunities
    • Office Life and Perks

      • Commuter Benefits Program
      • Casual Dress
      • Pet-friendly Office
      • Snacks
      • Some Meals Provided
      • On-Site Cafeteria
    • Vacation and Time Off

      • Paid Vacation
      • Paid Holidays
      • Personal/Sick Days
      • Leave of Absence
      • Volunteer Time Off
    • Financial and Retirement

      • 401(K) With Company Matching
      • Company Equity
      • Performance Bonus
      • Financial Counseling
    • Professional Development

      • Tuition Reimbursement
      • Internship Program
    • Diversity and Inclusion

      • Employee Resource Groups (ERG)

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