Software Engineer II, ML Experimentation

2 Days ago • 1 Years + • Backend Development • Full Stack Development

Job Summary

Job Description

As a Software Engineer II on the ML Experimentation team at YouTube (a Google company), you'll design and build tools to enhance ML research and development. This includes improving the tools used daily by ML researchers and developers, creating new tools, iterating on existing ones, and collaborating effectively across teams. Key responsibilities involve accelerating the process of building and packaging code, securing access and scheduling on TPUs, and designing solutions to improve ML research and development workflows. You'll contribute directly to the enhancement of Google's machine learning capabilities and help shape the future of YouTube's technological infrastructure.
Must have:
  • Bachelor's degree or equivalent experience
  • 1 year software development experience (Python, C++, Java etc.)
  • 1 year experience with data structures/algorithms
  • 1 year experience building large-scale infrastructure
  • Design and build solutions to improve ML research and development
Good to have:
  • Experience with large-scale distributed systems (e.g., Slurm, Borg)
  • Experience with build systems (e.g., Blaze, Bazel)
  • Experience improving system performance (profiling, optimization)
  • Experience with ML/AI infrastructure and Python
  • Experience building developer tools

Job Details

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  • 1 year of experience with data structures or algorithms.
  • 1 year of experience building and developing large-scale infrastructure or distributed systems.

Preferred qualifications:

  • Experience with large scale distributed systems and scheduling infrastructure (e.g. slurm, borg, xborg, flume).
  • Experience with build systems and infrastructure (e.g. blaze, bazel, etc.).
  • Experience in improving system performance (e.g., profiling, system optimization).
  • Experience with ML/AI (Infrastructure) and Python.
  • Experience in building developer tools.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

As part of the Machine Learning (ML) Experimentation team, you will design and build solutions to improve ML research and development.At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.

Responsibilities

  • Enhance the tools ML researchers and developers use every day and build new ones and iterate on new ideas and collaborate across teams.
  • Work on efforts to speed up the process to solve building and packaging code, getting access and scheduling on TPUs.
  • Design and build solutions to improve ML research and development.

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