AI​/Machine Learning Research Scientist; Remote Eligible

Annual Salary Range: $ – $

Work‑Site Type:
Remote

We are seeking a Machine Learning Research Scientist who will support the development of fundamentals for GeoAI imagery processing, self‑supervised learning methods for large vision‑language models to enable downstream imagery perception tasks including object detection and counting, visual question answering, semantic segmentation, and change detection. This position resides in the GeoAI Research Group in the Geographic Data Science Section, Geospatial Science and Human Security Division, National Security Sciences Directorate, at Oak Ridge National Laboratory (ORNL).

As part of our team, you will support research tasks related to image preprocessing pipelines including pan sharpening, geocoding, atmospheric compensation, image denoising, cloud masking, fine tuning large geospatial foundation models for a variety of national security downstream tasks. The GeoAI Group is part of the Geospatial Science and Engineering Division (GSED)  group conducts cutting‑edge research and publishes from novel machine‑learning based solutions to large‑scale geospatial application solutions.

Research activities include the design of efficient image preprocessing pipelines, machine‑learning workflows using high performance computing techniques, and conducting post‑processing and validations of model outcomes. Under the guidance of senior research scientists, the selected applicant will take roles on multidisciplinary teams supporting cutting‑edge research and engineering projects, deploying workflows on large‑scale computing environments, leveraging ORNL's Frontier for its dense GPU‑based high‑performance computing resources to train large GeoAI models.

• Develop and execute accelerated imagery preprocessing pipelines for high‑resolution satellite imagery
• Develop and execute workflows to support fine tuning large geospatial vision models
• Collect, process, and analyze large volumes of satellite imagery
• Support the design and implementation of efficient computer vision techniques
• Visualize and communicate research results through technical reports, and peer‑reviewed publications
• Collaborate with other research and technical professionals on new methods to advance GeoAI methods
• Deliver strong science and engineering artifacts demonstrating research innovation for our sponsors
• Enable ORNL's mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote diversity, equity, inclusion, and accessibility by fostering a respectful workplace—in how we treat one another, work together, and measure success

• A PhD degree in electrical engineering, civil engineering, geoinformation science, or a related discipline
• A minimum of 4 years of applied experience
• Hands‑on experience with training machine learning models on high performance computing infrastructures leveraging GPU accelerators
• Experiences building satellite imagery preprocessing workflows
• Experience using Python or other programming languages to develop AI algorithms in PyTorch computing framework

• Experience working with spatio‑temporal datasets and remote sensing imagery
• Knowledge of distributed computing and uncertainty quantification
• Ability to function well in a fast‑paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs

• Visa sponsorship is not available for this position.
• This position requires the ability to obtain and maintain a Secret Compartmented Information (SCI) 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. In addition, due the SCI, you may also be subject to random polygraph testing.

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.

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.