Data Systems AI / ML Engineer

Oak Ridge National Laboratory; Oak Ridge (TN); On-site; USD 110,000 - 150,000; Full time

Job summary

Oak Ridge National Laboratory (ORNL)Environmental Sciences Division seeks a Data Systems AI/ML Engineer for the Earth Sciences Informatics portfolio. You will build AI-driven methods to make ARM data easier to find and use, and design conversational interfaces powered by large language models to help researchers discover data intuitively.

You will work with a collaborative team to develop training datasets from ARM metadata records and deploy AI/ML solutions from prototype to production,

Qualifications

• BS/MS in computer science, data science, AI, or closely related field with 1–2 years of relevant experience
• Two years of Python programming experience for data processing, scripting, or ML workflows
• Familiar with core ML concepts (supervised/unsupervised learning, embeddings, model evaluation) and information retrieval concepts

Responsibilities

• Research, develop, and deploy AI/ML methods, including LLM-based conversational interfaces and retrieval systems
• Build and maintain training and evaluation datasets from ARM metadata
• Collaborate with data scientists, software engineers, and DevOps to move systems from prototype to production
• Support researchers and developers in creating tools for the ARM Data Center
• Grow into a leadership role in AI/ML engineering through deliverables, presentations, and collaborations across the ARM community

Skills

Python

ML concepts

NLP/LLMs

REST APIs

Docker

Git workflows

Data retrieval

Education

Bachelor's in CS/Data Science/AI

Tools

PyTorch

TensorFlow

Hugging Face

LangChain

Milvus

PGVector

Job description

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The Environmental Sciences Division (ESD) at Oak Ridge National Laboratory (ORNL) is seeking a Data Systems AI/ML Engineer for its Earth Sciences Informatics portfolio. In this role, you will develop AI-driven methods that make data from the Atmospheric Radiation Measurement (ARM) user facility easier to find and use.

You will build training datasets from years of ARM metadata records and design and implement conversational interfaces powered by large language models (LLMs) that help researchers discover data intuitively and efficiently. You will work as part of a collaborative team and pursue independent research and development.

The ARM Data Center processes, archives, and distributes atmospheric observations from observatories around the globe, and provides computing infrastructure and analysis tools to the scientific community. Your work will directly improve how that community accesses and uses these data.

Major Duties and Responsibilities

• Research, develop, and deploy AI/ML methods, including LLM-based conversational interfaces and retrieval systems, that improve discovery and usability of ARM data.
• Build and maintain training and evaluation datasets derived from ARM metadata records.
• Work with data scientists, database engineers, software engineers, and DevOps engineers to take systems from prototype to production.
• Support researchers and developers in creating tools for the ARM Data Center.
• Grow into a leadership role in AI/ML engineering for the group, demonstrated through deliverables to sponsors, platform development, technical presentations and demonstrations, and, where appropriate, inventions, patents, or copyrights.
• Identify and pursue opportunities to expand existing AI/ML workflows and start 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.

Basic Qualifications

• 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.
• Two 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.

Preferred Qualifications:

You are not expected to have all of these. Depth in a few areas is more valuable than shallow coverage of all of them.

LLMs and retrieval

• Experience with natural language processing (NLP) or LLMs, through work or coursework.
• Retrieval-augmented generation (RAG), agentic RAG, or agent-based AI systems.
• Embeddings, semantic search, and prompt development.
• Orchestration frameworks such as LangChain or Agno.
• Familiarity with or interest in protocols for LLM tool integration and context exchange, such as the Model Context Protocol (MCP).
• Vector databases or search engines such as PGVector or Milvus, and knowledge of indexing, ranking, and similarity search.

ML and evaluation

• Python scientific stack (NumPy, pandas, scikit-learn) and Jupyter notebooks for exploration and prototyping.
• 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.
• Logging, tracing, and performance monitoring for AI systems.

Backend and engineering

• RESTful API development with FastAPI, Flask, or similar frameworks, and experience integrating AI services into backend systems or data pipelines.
• Git and collaborative development workflows.
• Familiarity with Docker.

Scientific data

• Experience with scientific datasets, metadata standards, or data catalogs.
• Knowledge of FAIR (Findable, Accessible, Interoperable, Reusable) data principles and reproducible research practices.
• Interest in atmospheric science or Earth system data. Domain expertise is not required.

Special Requirements

• Visa sponsorship is not available for this position.
• For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant 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 check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.

About ORNL

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.

Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.

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This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.