Design and deliver AI/ML decision-making frameworks and generative models to drive business outcomes.
Responsibilities
Develop and fine-tune NLP models for summarization, Named Entity Recognition (NER), text classification, and sentiment analysis on unstructured clinical records.
Implement dynamic prompt engineering strategies to optimize generative AI model outputs.
Analyze and preprocess large datasets, including physician notes and discharge summaries.
Design and implement data pipelines and structure SQL and NoSQL databases for efficient retrieval.
Deploy AI models into cloud-based production environments using Docker and CI/CD pipelines.
Required Skills
6+ years of experience in AI/ML development with a focus on NLP and Generative AI.
Expertise in Python and frameworks including TensorFlow, PyTorch, and Hugging Face.
Hands-on experience with generative models such as OpenAI’s GPT and LLaMA.
Proficiency with Transformers, NLTK, SpaCy, Gensim, Pandas, and NumPy.
Experience with cloud platforms (AWS, Azure) and containerization using Docker.
Knowledge of SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Elasticsearch) databases.
Familiarity with healthcare data standards including HL7, FHIR, ICD codes, and SNOMED.
Experience implementing prompt engineering and human-in-the-loop systems.
Preferred Skills
Master’s degree in Data Science, AI, or Computer Science with 10+ years of experience, or a PhD with 4+ years of experience.