AI Engineer for Clinical NLP

We are looking for an experienced NLP focused AI Engineer to help us unlock insights from clinical notes, care plans, and patient documentation. The resource will work with transformer models and rule based techniques to enable AI driven personalized care, behavioral analysis, and nonadherence detection.

Responsibilities

• Build NLP pipelines to extract symptoms, conditions, behaviors, and clinical context
• Fine tune and deploy models like ClinicalBERT, BioBERT, or BlueBERT
• Implement sectionizers, negation detection, and temporal classifiers using tools like MedSpaCy
• Contribute to hybrid models that combine unstructured and structured patient data
• Support generation of personalized care interventions
• Collaborate with ML engineers, clinical analysts, and developers
• Ensure compliance with healthcare standards (HIPAA)

Required Skills

• 3+ years of NLP/ML experience
• Hands on experience with transformers and fine tuning pretrained models
• Strong programming background in Python
• Experience working with PyTorch/TensorFlow
• Experience working with libraries like spaCy and Hugging Face Transformers
• Understanding of context detection, classification, and named entity recognition
• Deployment experience in Azure, AWS or GCP

Nice To Have Skills

• Experience with healthcare chatbots
• Prompt engineering or experience working with LLMs
• Knowledge of early warning scores and risk stratification
• Familiarity with clinical terminology and standards like ICD-10