Senior Machine Learning Software Engineer
Imagen is extending the frontiers of radiology and artificial intelligence (AI) to improve human well-being. In the short term, we are building state-of-the-art AI software to reduce diagnostic errors in radiology and improve patient outcomes. Over the long term, we are transforming early disease identification and management through our interdisciplinary research at the intersection of medicine and AI.
We’re a team of leading scientists, engineers, clinicians, and industry professionals from some of the top healthcare and technology organizations across the globe. Our clinical team is comprised of radiologists and surgeons from Mayo Clinic, Stanford Hospital, Hospital for Special Surgery, Boston Children’s Hospital, and other prestigious institutions. Imagen’s technical team is comprised of machine learning PhDs and engineers with extensive experience doing research and building technology and products at leading companies, including Google and Facebook.
We were founded in 2016 and have raised over $60M from leading venture capitalists, hospitals and health systems, and technology entrepreneurs. Our institutional investors include Google Ventures and DFJ.
As Senior Machine Learning Software Engineer, you will work with a small team of scientists, radiologists, and software engineers who plan and develop Imagen’s machine learning products. You will be helping design and rapidly prototype our machine learning software, including the tools and infrastructure necessary to build and deploy it at healthcare providers. You’ll be focused on rapid prototyping and iteration, making practical implementation decisions, and creating proofs of concept for novel research ideas.
On a day to day basis, you’ll tackle questions like the following:
- What's the best way to take a prototype Python model and move it into production use at scale?
- How can we help our scientists create reproducible research and be collaborative?
- How can we best make use of petabyte-scale medical image datasets using AI?
- How can we make various types of data, such as de-identified radiology reports, available for our machine learning pipelines?
The ideal candidate will have:
- Extensive experience at enabling machine learning software or analytics, building infrastructure or products to support it
- Extensive experience practicing machine learning, having developed and deployed your own models
- Knowledge of AWS or GCP technologies and services
- Good communication skills and a strong sense of pragmatism
- Scrappiness and an ability to deal with ambiguity, a passion for solving interdisciplinary problems, and a growth mindset
This role will report directly to our Co-founder and Chief Science Officer.