Minimum qualifications:

  • Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
  • 3 years of software development experience with a general purpose programming language, including Java, C/C++, C#, Objective C, Python, JavaScript, or Go.
  • Ability to speak and write in English fluently.

Preferred qualifications:

  • Experience leading designs of major software components, systems, and features.
  • Product engineering experience in building front end/full stack web apps.
  • Experience with modern web stack and data visualization.

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.

TensorFlow Extended (TFX) is a Google-production-scale machine learning platform based on TensorFlow. It provides a configuration framework and shared libraries to integrate common components needed to define, launch, and monitor your machine learning system. It is used extensively both within Google as well as outside. TFX team is now a part of Frameworks and Services organization in Core Machine Learning (ML). We’re building the next generation ML pipeline and its web frontend. We’re also developing pipelines for on device ML models. We’re converting our infrastructure to support Alphabet wide, centralized managed training service for production.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.


  • Build reliable, scalable and efficient infrastructure for machine learning training, including pipelines, workflows and services.
  • Collaborate with clients teams to help design and implement subsystems to solve their problems and integrate with TFX.
  • Collaborate with other ML Infrastructure teams across Alphabet to build next-generation of machine learning platform portable across Alphabet, Google Cloud and Open source.