ML Research Engineer

About us

Layer Health is an AI startup spun out of MIT CSAIL, revolutionizing clinical documentation by leveraging the power of large language models. Having deployed our technology in real-world health systems, we've witnessed how the difficulty of accurately and efficiently extracting information from clinical notes affects all aspects of healthcare. We are building an AI layer that will radically speed up and improve the quality of extracting and synthesizing information from medical records, with the mission to reduce friction everywhere in healthcare, power the future of precision medicine, and ultimately improve patient outcomes. Our diverse founding team brings expertise across machine learning, large language models, medicine, and human-computer interaction.

We’re seeking outstanding hires to join our seed-stage stealth company as early members. Together, we will create the AI layer that will redefine healthcare for the better.

Job Description

We’re hiring an experienced ML Research Engineer to join our team. In this role, you will help support our growing engineering efforts by building efficient and scalable ML tooling.

You can expect to:

• Research, develop, and productionize LLM-powered machine learning methods for extracting insights from longitudinal clinical data (both unstructured and structured).
• Build efficient research infrastructure tooling to supercharge our R&D efforts (includes benchmarking, training, prototyping new features, curating high-quality ground truth data, etc.).
• Translate start-of-the-art models (both internally developed and from the community) into production, delivering value for our customers.
• Work with large-scale, real-world clinical data, developing solutions to better parse and interpret it.
• Develop methods and features to ensure high-quality results for our production models (methods to detect drift/performance degradation; develop observability tooling for performance characteristics, etc.).
• Collaborate with the broader product, engineering, and research teams to improve our products and build the next-generation of ML for healthcare.

We look for:

• A minimum of 5 years of experience as an ML Engineer and/or Research Engineer (applied research, not theoretical).
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field.
• Proficiency in Python or other programming languages commonly used in AI/ML development.
• Fluency with Python and other tooling/ML/NLP libraries (PyTorch, Tensorflow, HuggingFace, etc.). 
• Strong problem-solving skills and attention to detail.
• Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
• Experience developing and maintaining performant, scalable, and data-centric enterprise software products.
• A strong communicator who thrives in a customer-focused, fast-paced environment. 
• An excited and adaptable team player who wants to disrupt the healthcare industry with AI/ML, alongside an awesome team. 
• We are a Boston-based company, and expect engineers to meet regularly in-person in either our NYC or Boston office (engineers from Boston, NYC, or east coast are welcome).

Join us and help us transform healthcare with AI. Layer Health is committed to foster an environment of inclusion that is free from discrimination.  We are an Equal Opportunity Employer where employment is decided on the basis of qualifications, merit, and business need. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected Veteran status, or any other characteristic protected by law. 

Expected compensation range for this role is $155,000-190,000 for Boston and NYC-based candidates; range may vary for candidates outside of the Boston/NYC metro area. Compensation is dependent on experience, overall fit to our role, and candidate location. Expected compensation ranges for this role may change over time. If your compensation requirement is greater than our posted salary ranges, please still consider applying to our role. We will make a determination as to whether an exception can be made.