AI/Machine Learning Research Scientist (Remote Eligible)

Requisition Id 16762 Annual Salary Range:$$145,170.00 -$$177,430.00 Work-Site Type: Remote ORNL offers a flexible work environment that supports both the organization and the employee. In addition, this position is considered remote-eligible for ORNL in pre-approved locations. Remote-eligibility is not a continued guarantee and could be subject to change based on evolving organizational needs. Note about pay range: Please note that the pay range information is a general guideline only. Many factors are taken into consideration when setting starting pay. Salary for this position will be commensurate with the final candidate’s qualifications and experience, including skills, knowledge, relevant education, certifications, plus also aligned with the internal peer group. It is not typical for an individual to be offered a salary at or near the top of the range for a position. Link to benefits. Overview: 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 pansharpening, geocoding, atmospheric compensation, image denoising, cloud masking, finetuning 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) at ORNL. The 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 of 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. Major Duties/Responsibilities: Develop and execute accelerated imagery preprocessing pipelines for high resolution satellite imagery Develop and execute workflows to support finetuning 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 Basic Qualifications: 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 Preferred Qualifications: 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 Special Requirements: 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. 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. 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. We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment. If you have trouble applying for a position, please email View email address on click.appcast.io. 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.