Machine Learning Engineer

About us:

Layer Health is an AI startup spun out of MIT, revolutionizing chart review for healthcare. Using the latest LLM technology, we are vastly improving the value and impact that can be unlocked from medical record data.

We know that all organizations in the healthcare ecosystem struggle to extract and synthesize insights from medical charts at scale. Our AI layer radically speeds up and improves the quality of information gleaned from these medical records to power a wide range of impactful use cases from research to quality measurement to clinical care pathways.

Our diverse founding team brings expertise across machine learning, large language models, medicine, and human-computer interaction.

We're currently hiring a Machine Learning engineer in our Boston or NYC office (hybrid). As a Machine Learning Engineer at Layer Health, you will design, develop, and deploy machine learning models and systems to address real-world challenges in our industry. You will work closely with our software engineers, data scientists, researchers and product teams to integrate ML solutions into our platform, ensuring scalability, efficiency, and reliability. This is an opportunity to contribute to a high-impact team and help define the next stage of a major growth inflection point for Layer Health.

You can expect to:

• Develope and productionize LLM-powered machine learning models used to power efficiency and learning of clinical patient notes understanding
• 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 (both structured and unstructured 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.
• Build scalable infrastructure to ensure we can scalably support efficient model development and deployment pipelines, CI/CD, testing / experimentation.
• Ensure robust monitoring, logging, and error handling for deployed systems.
• Stay updated on the latest advancements in machine learning and AI.
• Experiment with state-of-the-art techniques and evaluate their applicability to our needs.

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 $190,000-220,000 for Boston or NYC-based candidates; range may vary for candidates outside of the NYC/Boston 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.