Description

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.

Key Skills

Education

Master's degree