Machine Learning Research Engineer, Health AI

3 Months ago • 2 Years + • Artificial Intelligence

Job Summary

Job Description

Google's Health AI team seeks a Machine Learning Research Engineer to innovate, implement, and evaluate ML algorithms using multimodal healthcare data. Responsibilities include authoring research publications, designing and implementing complex research infrastructure, manipulating large medical datasets, and collaborating with various stakeholders (Product Managers, Clinicians, UX researchers). The role involves advancing foundational ML capabilities (multimodality, reasoning, safety) and building agents for breakthrough capabilities in healthcare. The ideal candidate possesses experience with machine learning, data structures, algorithms, and at least one research publication. Experience with generative AI, deep learning, and health domain expertise are preferred.
Must have:
  • Bachelor's degree or equivalent experience
  • 2+ years software engineering experience or 1 year with advanced degree
  • 2+ years experience with data structures/algorithms
  • Machine learning experience
  • Research publication submissions
Good to have:
  • Experience fine-tuning generative AI models
  • Deep Learning experiment experience
  • Machine learning in healthcare experience
  • JAX, TensorFlow, or PyTorch knowledge
  • Interest in healthcare research application

Job Details

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 2 years of experience with software engineering in one or more programming languages, or 1 year of experience with an advanced degree.
  • 2 years of experience with data structures or algorithms.
  • Machine learning experience.
  • One or more research publication submissions for conferences, journals, or public repositories.

Preferred qualifications:

  • Experience with fine-tuning and evaluating generative AI models.
  • Experience conducting Deep Learning experiments.
  • Experience with machine learning in the health domain.
  • Working knowledge of JAX, TensorFlow, or PyTorch.
  • Interest in the application of research to healthcare.

About the job

At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.

Health AI's mission is to catalyse the adoption of human-centred AI in healthcare and medicine. We see AI as transformational in these fields, and a necessary component in realizing personalized medicine, expanding access for underserved populations, improving quality and consistency, deploying care at the edge, and closing the loop of a learning healthcare system.

The Health AI India team conducts machine learning (ML) research as part of a broader multidisciplinary effort. As part of this team in Health AI, you'll have opportunities to advance foundational ML capabilities (e.g., multimodality, reasoning, safety, interpretability, memory) and build agents to enable breakthrough capabilities, and pioneer next-generation experiences in collaboration with other teams in consumer health and adjacent domains such as education.

Responsibilities

  • Innovate, implement and evaluate machine learning algorithms over multimodal healthcare data.
  • Author publications of novel research in leading scientific journals and conferences.
  • Design, implement and deliver complex pieces of research and infrastructure as part of a multi-disciplinary team.
  • Manipulate and evaluate large and complex medical datasets.
  • Work with a variety of internal and external stakeholders, including Product Managers, Clinicians, UX researchers and Regulatory Advisors.

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