VideaHealth is a cutting-edge AI-powered solution for dentistry, developed by a team of seasoned leaders, engineers, AI scientists, and clinicians spun out of MIT. Our vision is to be the first company to diagnose a billion people globally. Our product is already used by thousands of dental clinicians to improve the quality of care through faster diagnoses, increase operating efficiencies, and improved patient understanding.
We are looking for a Senior Machine Learning Engineer to join our growing ML team. This is an exciting opportunity to contribute and grow your technical skills by building end to end highly impactful software medical devices that will ultimately impact the lives of millions of people.
In this role, you’ll take full ownership of high-impact projects and design robust infrastructure that powers our clinical applications, from computer vision models to decision support systems. You’ll work side-by-side with our leadership team and collaborate across a dynamic, tight-knit team that thrives on innovation and execution. You’ll have the opportunity to work at the cutting edge of AI and healthcare, in close collaboration with renowned advisors from MIT and Harvard, and alongside researchers, physicians, and regulatory experts, including those with deep FDA experience.
We’re looking for a hands-on ML expert who’s excited to build, ship, and own real-world products. If you're a builder with a passion for impact, eager to grow fast and help define the future of AI in healthcare — we’d love to meet you.
Own the design and implementation of infrastructure for reliable and highly performant deep learning and analytics pipelines with the main focus on the detection and classification of dental conditions from images.
Research, prototype, and deploy production-grade computer vision models (e.g., CNNs, transformers)
Play a critical role in defining and executing processes for managing large amounts of data, defining data sampling approaches and performance evaluations.
Write traceable, testable, and reproducible code to support FDA/CE-cleared ML workflows. Collaborate on documentation for 510(k) submissions.
Design model monitoring tools for drift detection, explainability, and performance in production.
Partner with clinical experts and software engineers to ensure models are safe, effective, and usable in real-world healthcare environments.
Minimum of 4 years of hands-on development building deep learning models
Experience with at least one deep learning framework (e.g. PyTorch, TF, Keras)
Strong software development skills including testing (Python) and leading development in a shared codebase
Strong communication and collaboration skills
M.S. or PhD in Computer Science or related field.
Experience in reading & implementing technical research papers
Proven track-record of high quality software development (e.g. on GitHub)
Experience in working with medical images or related Computer Vision problems
Experience in Data Analysis (e.g. statistics, performance metrics)
Experience working with cloud based platforms / providers (e.g. AWS)
Fast paced and collaborative work culture in which you can gain experience, grow your technical skills and work on a wide variety of challenges over your time with us
Competitive pay, equity and benefits (flexible PTO)
Agile organization where being senior translates to being a mentor and role model for others. We lead by example.
Technical challenges on the leading edge of innovation where software and machine learning intersect.
VideaHealth is supported by some of the best investors in the world, having raised over $67M in Venture Capital from Tier 1 investors such as Spark Capital (Twitter, SnapChat, SmileDirectClub), Zetta Venture (Kaggle), and Pillar VC (PillPack), as well as angel investors such as Frederic Kerrest (Co-founder of Okta). Our work has been featured in TechCrunch, Wall Street Journal, and many other outlets.
If you want to join a breakthrough healthtech company and help accelerate its impact and growth, we encourage you to apply for this exciting opportunity!
Originally posted on Himalayas
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