AI / ML Engineer

Develop and productionize advanced AI/ML solutions, including LLM training and fine-tuning, GraphRAG, embeddings, semantic retrieval, distributed multi-GPU training, and reinforcement learning alignment. Build hybrid NLP systems, optimize model architectures and retrieval pipelines, and collaborate cross-functionally to deploy AI solutions. The role requires deep expertise in machine learning, deep learning, NLP, transformer and state-space architectures, cloud ML platforms, data preparation, and production-grade model development.

Designs and operates enterprise-scale AI/ML platforms for prior authorization automation. Responsibilities include building MLOps pipelines, ML deployment frameworks, lifecycle management, CI/CD, automated retraining, model and data-drift monitoring, hallucination tracking, champion-challenger frameworks, observability, governance, compliance, and responsible AI controls. The role requires strong Python, Azure ML, Databricks, MLflow, cloud, and production ML operations experience.

Leads the design, training, optimization, and production deployment of advanced AI/ML systems, including LLMs, GraphRAG pipelines, embeddings, semantic retrieval, NLP, reinforcement learning, and distributed multi-GPU training. Translates research into scalable clinical AI solutions, collaborates with cross-functional teams, and advances methods for information extraction, document understanding, and summarization. Requires deep machine learning expertise, production experience, strong programming skills, and a substantial publication record.