Software Engineer, Machine Learning, Health AI

November 27, 2022
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Job Description

Batch – 2023/2022/2021/2020 and earlier

Minimum qualifications:

  • Master’s degree or PhD in Machine Learning or equivalent practical experience.
  • Experience in Machine Learning software engineering projects.

Preferred qualifications:

  • Experience in Machine Learning in the healthcare domain.
  • Experience in conducting learning experiments.
  • Experience in application of research to healthcare.
  • Knowledge of TensorFlow.

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.

Google Health is a company-wide effort to help billions of people be healthier. We work toward this vision by meeting people in their everyday moments and empowering them to stay healthy and partnering with care teams to provide more accurate, accessible, and equitable care. Our teams are applying our expertise and technology to improve health outcomes globally – with high-quality information and tools to help people manage their health and wellbeing, solutions to transform care delivery, research to catalyze the use of artificial intelligence for the screening and diagnosis of disease, and data and insights to the public health community.


  • Design, implement, and deliver complex pieces of research and infrastructure as part of a multi-disciplinary team.
  • Implement and evaluate cutting-edge machine learning algorithms over healthcare data.
  • Manipulate and evaluate large and complex medical datasets.
  • Work with a variety of internal and external stakeholders, including Product Managers, Research Scientists, Clinicians, UX researchers, and Regulatory Advisors.
  • Contribute to the application of research in product, and publication of results in leading scientific journals.