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Software Engineering Manager, AI/ML Infrastructure and Performance Engineering

Google· AI/ML Infrastructure and Performance Engineering (MSCA)
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Hybrid (Bengaluru)Full-timePosted 3w ago

About the role

Software Engineering Manager responsible for leading technical teams focused on performance optimization and ML infrastructure, with ownership of outcomes, influencing stakeholders, and guiding product and people management across multiple teams and locations.

Responsibilities

  • Learn and build an intuitive understanding of existing data collection, analysis, and visualization workflows with deep introspection across Frameworks, Accelerated Linear Algebra (XLA) and runtime stack.
  • Support new ML paradigms (such as horizontal scaling for upcoming TPU chips) by contributing across the end-to-end stack and analysis tools; partner with ML Stack leads to understand model optimization use cases and bring debugging to 3P environments (VSCode, Cursor, Grafana, etc).
  • Work with OSS ML inference frameworks such as vLLM, SGLang to provide insights in Xprof about performance improvement opportunities.
  • Partner with other teams that own various parts of the ML stack to understand performance optimization use cases; work with OSS ML inference frameworks such as TorchTPU, vLLM, SGLang to provide insights into performance bottlenecks.

Qualifications

  • 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.

Skills

Required:Software engineering leadershipMachine learning infrastructurePerformance optimizationML frameworks (TensorFlow, JAX, PyTorch, Keras)
Nice to have:Open-source software development
Last updated Oct 23, 2026. Interested? Apply on the company site.

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