AI​/ML Engineer

Requisition Id15724

Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security. The Data Science & Visualization Group at Oak Ridge National Laboratory (ORNL) advances AI/ML research and delivers applied solutions that support high-impact national security missions.

We are seeking 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. You will partner with multidisciplinary researchers across ORNL and external collaborators to enable data-driven decision‑making in a variety of contexts. This position resides in the Data Science & Visualization Group in the Advanced Intelligent Systems Section, Cyber Resilience and Intelligence Division, National Security Sciences Directorate, at Oak Ridge National Laboratory (ORNL).

• Develop AI/ML models and systems for diverse data and mission contexts
• Design and implement reproducible pipelines for data acquisition, feature engineering, model training, evaluation, packaging, and deployment
• 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

• Master’s degree in Computer Science, Data Science, Applied Mathematics, or a related field.
• Strong Python development skills and familiarity with git, CLI tooling, VS Code
• Proficiency with PyTorch and/or Tensor Flow, along with other Python ML development packages; experience building, training, evaluating ML/DL models
• Demonstrated ability to design statistical analyses and experiments (e.g., hypothesis tests, confidence intervals)
• Experience implementing reproducible data/model pipelines and documenting assumptions, parameters, metrics, and results

• Experience with predictive modeling and generative AI/LLMs, including RAG systems
• Familiarity with LLM inference servers (e.g.,
  vLLM , Ollama
  )
• Hands‑on benchmarking/Test & Evaluation of AI systems
• Data visualization and dashboarding (e.g., Streamlit)
• 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

• Q Clearance:
  This position requires the ability to obtain and maintain a clearance from the Department of Energy. As such, this position is a Workplace Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre‑placement drug test and participation in an ongoing random drug testing program.

For employment at Oak Ridge National Laboratory (ORNL), a Real  form of identification will be required. Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post‑employment background investigation.

To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background…