Oak Ridge National Laboratory
Machine Learning Research Engineer (Hybrid Eligible)
Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States, 37830
Machine Learning Research Engineer (Hybrid Eligible)
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Machine Learning Research Engineer (Hybrid Eligible)
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Oak Ridge National Laboratory
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Overview 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.
Requisition Id 15347
Level: RP02
Major Duties/Responsibilities
Deploy large-scale production workflows to support high-volume of sponsor imagery feature requirements.
Develop and implement production workflows for infrastructure damage assessment and change monitoring.
Handle high-cadence sponsor data deliverables.
Scaling of deep neural network inference and deploying tools for polygonization of building footprint vector geometries.
Develop and implement workflows to support large scale self-supervising learning for large vision-language models.
Collect, process, and analyze large volumes of high-resolution satellite imagery.
Support the design and implementation of efficient finetuning methods for deploying task specific foundation models.
Visualize and communicate analysis results via technical reports, and peer-reviewed publications.
Collaborate with other research and technical professionals on new methods to advance GeoAI for end-to-end multi-modality geospatial data analytics.
Deliver strong science and engineering artifacts demonstrating research innovation for our sponsors.
Performing workflow containerization and liaisons for stakeholder software deliverables.
Basic Qualifications
MS or PhD in electrical engineering, civil engineering, geoinformation science, or a related field and two (2) years of applied experience (professional or academic lab setting).
Hands‑on experience training machine learning models on Earth observation imagery and HPC infrastructures using GPU accelerators.
Experience building data‑fusion workflows to ingest multi‑modality geospatial data.
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, quality control and assessment of satellite imagery derived products.
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 Q clearance.
Security, Credentialing, and Eligibility Requirements 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. For foreign national candidates: if you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three‑year residency requirement, you will be required to obtain a PIV credential to maintain employment.
Benefits at ORNL ORNL offers competitive pay and benefits programs to attract and retain dedicated people! The laboratory offers many employee benefits, including medical and retirement plans and flexible work hours, to help you and your family live happy and healthy. Employee amenities such as on‑site fitness, banking, and cafeteria facilities are also provided for 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. If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: ORNLRecruiting@ornl.gov. In addition, we offer a flexible work environment that supports both the organization and the employee. A hybrid/onsite working arrangement may be available with this position. 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 ORNLRecruiting@ornl.gov. 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.
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Machine Learning Research Engineer (Hybrid Eligible)
role at
Oak Ridge National Laboratory
Get AI-powered advice on this job and more exclusive features.
Overview 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.
Requisition Id 15347
Level: RP02
Major Duties/Responsibilities
Deploy large-scale production workflows to support high-volume of sponsor imagery feature requirements.
Develop and implement production workflows for infrastructure damage assessment and change monitoring.
Handle high-cadence sponsor data deliverables.
Scaling of deep neural network inference and deploying tools for polygonization of building footprint vector geometries.
Develop and implement workflows to support large scale self-supervising learning for large vision-language models.
Collect, process, and analyze large volumes of high-resolution satellite imagery.
Support the design and implementation of efficient finetuning methods for deploying task specific foundation models.
Visualize and communicate analysis results via technical reports, and peer-reviewed publications.
Collaborate with other research and technical professionals on new methods to advance GeoAI for end-to-end multi-modality geospatial data analytics.
Deliver strong science and engineering artifacts demonstrating research innovation for our sponsors.
Performing workflow containerization and liaisons for stakeholder software deliverables.
Basic Qualifications
MS or PhD in electrical engineering, civil engineering, geoinformation science, or a related field and two (2) years of applied experience (professional or academic lab setting).
Hands‑on experience training machine learning models on Earth observation imagery and HPC infrastructures using GPU accelerators.
Experience building data‑fusion workflows to ingest multi‑modality geospatial data.
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, quality control and assessment of satellite imagery derived products.
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 Q clearance.
Security, Credentialing, and Eligibility Requirements 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. For foreign national candidates: if you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three‑year residency requirement, you will be required to obtain a PIV credential to maintain employment.
Benefits at ORNL ORNL offers competitive pay and benefits programs to attract and retain dedicated people! The laboratory offers many employee benefits, including medical and retirement plans and flexible work hours, to help you and your family live happy and healthy. Employee amenities such as on‑site fitness, banking, and cafeteria facilities are also provided for 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. If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: ORNLRecruiting@ornl.gov. In addition, we offer a flexible work environment that supports both the organization and the employee. A hybrid/onsite working arrangement may be available with this position. 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 ORNLRecruiting@ornl.gov. 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.
#J-18808-Ljbffr