ML Infrastructure Engineer
Layer Health is a stealth AI startup recently 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 exceptional engineers to join our seed-stage stealth company as early members. Together, we will create the AI layer that will redefine healthcare for the better.
We’re hiring an experienced ML Infrastructure Engineer to join our team. In this role, you will build systems to efficiently train and perform inference with large-scale machine learning models.
You can expect to:
- Design, build, and maintain scalable and performant APIs for model inference, fine-tuning, and training of large language models.
- Architect large-scale backend infrastructure for AI/ML tasks such as distributed compute, data engineering, data management, and model serving.
- Stay up-to-date on the latest in foundation model research and proactively integrate these technologies into the product where applicable.
- Establish and enforce best practices for data processing, analytics, machine learning infrastructure, and code development.
- Cultivate and foster a robust engineering and product culture that drives the company forward.
We look for:
- 4+ years of experience in building production-grade ML training and inference pipelines for cloud-native applications.
- Experience with distributed compute and deep learning frameworks, particularly for training and inference of large models.
- Knowledge of both statistical and modern deep learning (e.g. transformer) techniques and architectures.
- 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 Boston (engineers from Boston, NYC, or east coast are welcome).
Join us and help us transform healthcare with AI.