D. or advanced Masters degree in a relevant scientific or quantitative discipline Experience supporting NIH or other federal biomedical research organizations Experience applying large language models (LLMs) to scientific analysis, information extraction, summarization, or question answering Experience with Retrieval-Augmented Generation (RAG), embeddings, vector databases, and semantic search Experience evaluating AI systems using benchmark-driven and human-in-the-loop methodologies Experience analyzing publications, grants, patents, clinical trials, or other large-scale scientific datasets Familiarity with MLOps practices such as model versioning, monitoring, and lifecycle management in production environments Experience building AI prototypes or pilot applications in shared or enterprise environments Knowledge of data governance, security, and compliance considerations, particularly in regulated or federal environments Exposure to modern data platforms and distributed processing frameworks (e.g., Spark, Databricks) Strong communication skills with the ability to explain AI concepts and analytical findings to non-technical stakeholders Experience working in cross-functional or product-oriented teams to translate requirements into technical solutions. Minimum qualifications: Five to seven years of relevant experience with the items below: Strong programming and AI/ML development skills, including Python, experience with modern frameworks, and with integrating AI models into existing software architectures Experience designing and deploying AI solutions end-to-end, including integrating models into applications or shared infrastructure Strong background in algorithm design and data structures; comfort with software testing, debugging, and system architecture Solid data analysis and data engineering capability, including working with large datasets and translating findings into usable outputs Proficiency with cloud-based and containerized environments (e.g., AWS, Kubernetes) to support scalable AI workloads Ability to evaluate, iterate, and operationalize AI solutions, including performance measurement, experimentation, and collaboration with cross-functional teams Bachelor's degree in Computer Science, Software Engineering, Data Science or related quantitative area Ability to obtain a Public Trust Clearance.