Technial Lead Manager, ML Compiler, GPU

3 Months ago • 8-10 Years • Research & Development

Job Summary

Job Description

This role involves building compiler technology for machine learning frameworks at Google, including JAX, PyTorch/XLA, and TensorFlow. Responsibilities include enhancing the GPU software stack for performance and efficiency on cutting-edge ML workloads, launching new GPU optimizations, fostering collaboration with customers and partners, and developing team members in Zurich. The position requires managing engineers across multiple teams and locations, overseeing large-scale projects, and contributing to product strategy. The ideal candidate will have extensive experience in software development (Python, C, C++, Java, JavaScript), compiler technology (LLVM/MLIR, HPC compilation), and ML frameworks (TensorFlow, PyTorch, JAX, Spark ML), along with proven technical leadership and people management skills.
Must have:
  • 8+ years software development experience
  • 3+ years technical leadership
  • 2+ years people management
  • Experience with ML frameworks
  • Compiler technology expertise (LLVM/MLIR)
  • Enhance GPU performance
  • Launch GPU optimizations
  • Foster collaboration
Good to have:
  • Experience with TensorFlow, PyTorch, JAX, Spark ML
  • Experience with LLVM/MLIR and HPC compilation

Job Details

Minimum qualifications:

  • Bachelor's degree in Computer Science or equivalent practical experience.
  • 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  • 3 years of experience in a technical leadership role; overseeing projects, with 2 years of experience in a people management, supervision/team leadership role.

Preferred qualifications:

  • Experience designing and deploying with one or more from the following ML frameworks such as TensorFlow, PyTorch, JAX, Spark ML.
  • Experience working with compiler technology, specifically LLVM/MLIR and HPC compilation.

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.

In this role, you will build the compiler technology that powers machine learning frameworks at Google, including JAX, PyTorch/XLA and TensorFlow, and cutting-edge ML workloads like Gemini and next-generation Large-Language Models (LLMs). You will also build the MLIR compiler infrastructure and owns the XLA GPU compiler.

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

  • Enhance the GPU software stack so that it performs faster and more efficiently on cutting-edge ML workloads.
  • Launch new GPU optimizations end-to-end, including performance and correctness testing.
  • Foster deep collaboration between customers, partners (e.g. GPU manufacturers) and the GPU compiler team.
  • Support and develop members of the team and grow the team overall in Zürich.

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