Machine Learning Engineer, Healthcare NLP

Role overview Develop natural-language processing systems that extract useful, structured meaning from clinical notes, medical records, and other healthcare documents. The work applies modern language models and NLP methods to healthcare text at scale, with clinical experts helping validate system outputs.

Responsibilities - Design NLP pipelines for clinical text understanding and information extraction. - Build named-entity recognition systems for medical concepts and classification models for healthcare documents. - Turn unstructured notes into structured information, including entities and relationships. - Fine-tune and deploy large language models for healthcare applications. - Develop semantic search, summarization, generation, and documentation quality tools. - Work with clinical experts to assess output quality and improve accuracy.

Requirements - Strong foundation in NLP and machine learning. - Experience with transformer models and modern NLP architectures. - Experience using Python, PyTorch or TensorFlow, and NLP libraries. - Ability to work in ambiguous, real-world settings and communicate clearly. - High standards for model quality and delivered work.

Nice to have - Familiarity with clinical terminologies such as ICD, CPT, or SNOMED.

Benefits and work setup - Full-time role based in New Jersey or remote.