Data Systems AI / ML Engineer

Oak Ridge National Laboratory•Oak Ridge, TN

About The Position

The Environmental Sciences Division (ESD) at Oak Ridge National Laboratory (ORNL) is hiring a Data Systems AI/ML Engineer for its Earth Sciences Informatics portfolio. The role develops AI-driven methods that make data from the Atmospheric Radiation Measurement (ARM) user facility easier to find and use. The engineer will build training datasets from ARM metadata records and design and implement LLM-powered conversational interfaces to help researchers discover data intuitively and efficiently. The ARM Data Center processes, archives, and distributes atmospheric observations from observatories around the world and provides computing infrastructure and analysis tools to the scientific community. This position will improve how that community accesses and uses ARM data. The engineer will work collaboratively with a multidisciplinary team while also pursuing independent research and development, and will grow into a leadership role in AI/ML engineering for the group. Employment at ORNL requires Real ID-compliant identification and the ability to obtain and maintain a federal Personal Identity Verification (PIV) card. This includes successfully passing a Federal Tier 1 background investigation. Visa sponsorship is not available.

Requirements

A BS degree with at least 2 years of relevant experience, or an MS degree with at least 1 year of relevant experience, in computer science, data science, machine learning, artificial intelligence, environmental informatics, or a closely related field.
At least 2 years of Python programming experience, including data processing, scripting, or ML workflows; academic, research, and internship experience counts.
Working knowledge of core ML concepts, such as supervised and unsupervised learning, embeddings, and model evaluation.
Familiarity with structured data, metadata, or information retrieval concepts.
Interest in applying AI/ML to real-world scientific or environmental data problems.
Strong written and verbal communication skills and the ability to work in collaborative, research-oriented environments.
Ability to obtain and maintain a federal PIV card, including passing a Federal Tier 1 background investigation.
Real ID-compliant identification is required for employment at ORNL.

Nice To Haves

Experience with natural language processing (NLP) or LLMs through work or coursework.
Experience with retrieval-augmented generation (RAG), agentic RAG, or agent-based AI systems.
Experience with embeddings, semantic search, and prompt development.
Experience with orchestration frameworks such as LangChain or Agno.
Familiarity with or interest in LLM tool-integration and context-exchange protocols such as the Model Context Protocol (MCP).
Experience with vector databases or search engines such as PGVector or Milvus, and knowledge of indexing, ranking, and similarity search.
Experience with the Python scientific stack (NumPy, pandas, scikit-learn) and Jupyter notebooks for exploration and prototyping.
Experience with PyTorch or TensorFlow and libraries such as Hugging Face.
Experience evaluating or benchmarking ML or LLM-based systems, including experiment-tracking and monitoring tools such as MLflow or custom evaluation pipelines.
Experience with logging, tracing, and performance monitoring for AI systems.
Experience developing RESTful APIs with FastAPI, Flask, or similar frameworks, and integrating AI services into backend systems or data pipelines.
Experience with Git and collaborative development workflows.
Familiarity with Docker.
Experience with scientific datasets, metadata standards, or data catalogs.
Knowledge of FAIR data principles and reproducible research practices.
Interest in atmospheric science or Earth system data; domain expertise is not required.

Responsibilities

Research, develop, and deploy AI/ML methods, including LLM-based conversational interfaces and retrieval systems, to improve discovery and usability of ARM data.
Build and maintain training and evaluation datasets derived from ARM metadata records.
Collaborate with data scientists, database engineers, software engineers, and DevOps engineers to move systems from prototype to production.
Support researchers and developers in creating tools for the ARM Data Center.
Develop toward a leadership role in AI/ML engineering through sponsor deliverables, platform development, technical presentations and demonstrations, and, where appropriate, inventions, patents, or copyrights.
Identify and pursue opportunities to expand existing AI/ML workflows and initiate new ones.
Publish and present at workshops and conferences, and help build collaborations across the ARM community.
Follow and promote good practice in research integrity, AI/ML and software engineering, and safe and secure work in compliance with ORNL policies, standards, and procedures.