Layer Health is a company founded by leading machine learning researchers from MIT and Harvard Medical School, focused on building an AI layer to synthesize information from medical records. They are seeking an exceptional ML Engineer to design, develop, and deploy scalable ML software systems to address challenges in healthcare, collaborating with various teams to enhance their products.
Responsibilities:
- 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