Lead Machine Learning Engineer - Infrastructure

About us: Layer Health was founded in 2023 by leading machine learning researchers from MIT and Harvard Medical School. We are building an AI layer that can accurately and scalably synthesize information from medical records, with the mission to reduce friction everywhere in healthcare. Our LLM-powered platform is solving chart review once and for all, across use cases. For health systems, our first product dramatically accelerates clinical registry abstraction in areas ranging from surgery and cardiology, to oncology. Our long term vision is for our AI layer to safely transform patient care and minimize unnecessary heartbreak. Layer Health’s diverse founding team brings expertise across machine learning, UI/UX, large language models, and medicine. We’re seeking outstanding hires to join our team as early members. This is an opportunity to contribute to a high-impact, collaborative, mission-driven team, and help define the next stage of growth for Layer Health. Together, we will create the AI layer that will redefine healthcare for the better. We’re hiring an exceptional ML Infra Engineer to join our team (Boston or NYC office). You will work closely with our software engineers, research scientists, and product teams to build ML-native enterprise platforms, ensuring scalability, efficiency, and reliability. Here’s a collection of articles about our product, mission, recent funding round, etc. You can expect to: Architect efficient, secure, reliable, and performant ML pipelines and infrastructure. Design, develop, and maintain scalable/data-centric backend infrastructure for our product. Translate start-of-the-art LLM research (both internally developed and from the community) into production, delivering value for our customers. Work with complex, large-scale, real-world clinical data (both structured and unstructured data) in a cloud-based environment. 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. Cultivate a robust ML engineering and product culture that drives the company forward. We look for: 3+ years of experience in building ML-native backend infrastructure. 5-7+ years of experience in backend and cloud platform software development, with the ability and flexibility to traverse the stack when necessary. Fluency in one or more backend programming languages including Python, Golang, Rust, Java (we use Python). Familiarity with modern ML/LLM techniques and frameworks. Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field. Experience in 0-to-1 development of end-to-end ML systems (design, training, inference, deployment, and monitoring; bonus if involving LLMs). Experience developing and maintaining performant, scalable, and data-centric enterprise software products. Strong problem-solving skills and attention to detail. Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders. An excited and adaptable team player who wants to disrupt the healthcare industry with AI/ML, alongside an awesome team, in a customer-focused and fast-paced environment. We expect engineers to meet regularly in-person in either our NYC or Boston office (engineers from Boston, NYC, or east coast are welcome). Expected compensation range for this role is $210,000-260,000/year, in addition to stock options. Compensation is dependent on experience, overall fit to our role, and