Software Engineering Manager, AI/ML Infrastructure and Performance Engineering

Google; Bengaluru; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Google Bengaluru is seeking a Software Engineering Manager to lead and scale ML infrastructure efforts, focusing on performance, reliability, and collaboration across multiple teams. The role emphasizes building and guiding teams that optimize ML systems and hardware/software stacks.

You will drive project goals, contribute to product strategy, and help develop your engineers while operating across information retrieval, AI, distributed computing, and large-scale systems domains.

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 ML systems and applications.

Responsibilities

• Learn and build an intuitive understanding of existing data collection, analysis, and visualization workflows across ML stacks.
• Support ML paradigms by contributing across the end-to-end stack and analysis tools; partner with ML Stack leads.
• Work with OSS ML inference frameworks to provide insights on performance improvements.
• Partner with teams owning different parts of the ML stack to understand and address performance bottlenecks.

Skills

Software engineering

ML infrastructure

Distributed computing

People management

Debugging tools

Communication

Education

Bachelor's degree or equivalent

Tools

TensorFlow

JAX

PyTorch

Keras

vLLM

SG Lang

Pathways

Job description

Minimum 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.

Preferred qualifications

• 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.

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 is focused around driving continuous improvements to the machine learning software/hardware stacks through providing insightful performance debugging for workloads and custom kernels. We provide insights by summarizing different views of captured profile data - such as trace timelines, memory usage, Compiler profiles, ML graph summariesThe ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

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 and exciting ML paradigms (such as horizontal scaling for upcoming TPU chips) by making contributions across the end to end stack and analysis tools. Partner with ML Stack leads to understand model optimization use cases and bring debugging to feel native in 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.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.