Biometrics AI/ML Engineer

About the role

The Human Analysis and Biometrics (HAB) group at Oak Ridge National Laboratory (ORNL) seeks a technical contributor in AI/ML research to build models and pipelines, design and implement evaluations and benchmarks, and disseminate results through publications and briefings. This position resides in the Human Analysis and Biometrics Group in the Advanced Intelligent Systems Section, Cyber Resilience and Intelligence Division, National Security Sciences Directorate, at ORNL.

Major Duties/Responsibilities

• Contributes to requirements definition, design, and development of software applications in supporting the needs of projects as directed by the Principal Investigator and/or software team lead.
• Develop AI/ML models and systems for diverse data and mission contexts.
• Conduct independent and collaborative research in AI/ML, with a focus on multimodal learning, computer vision, and scientific machine learning.
• Design and implement reproducible pipelines for data acquisition, feature engineering, model training, evaluation, packaging, and deployment.
• Help the group envision, design, develop, test, and deploy human analysis and biometric recognition tools and prototypes.
• Conduct rigorous statistical analysis to aid in data exploration and interpretation.
• Benchmark and T&E AI/ML systems against performance metrics and robustness; define and implement measures of success for deployment-ready systems.
• Disseminate results via technical reports, publications, presentations, and sponsor briefings.
• Visualize and explain complex data and model results to technical and non-technical audiences.
• Contribute to research proposals and statements of work.
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service.
• Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.

Basic Qualifications

• A BS degree in computer science, computational science, data science, artificial intelligence, or related field.
• Experience with agile software development methodologies such as SCRUM.
• Strong foundation in machine learning, deep learning, or computer vision.
• Strong Python development skills and familiarity with git, CLI tooling, VS Code.
• Proficiency with PyTorch and/or TensorFlow, along with other Python ML development packages; experience building, training, evaluating ML/DL models.
• Experience implementing reproducible data/model pipelines and documenting assumptions, parameters, metrics, and results.

Preferred Qualifications

• Experience with predictive modeling and generative AI/LLMs, including RAG systems.
• Familiarity with LLM inference servers (e.g., vLLM, Ollama).
• Familiarity with high-performance computing (HPC) and distributed training environments.
• Interest in AI applications for safety, risk modeling, or scientific workflows.
• Excellent written and oral communication skills.
• Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory.
• Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs.