Senior Imagery Scientist – EO (TS/SCI)

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    "heading": "Senior Imagery Scientist – EO (TS/SCI)",
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    "description_html": "<span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><i><span style=\"font-family:Calibri, sans-serif;\">Artificial intelligence is rapidly changing how GEOINT is collected, analyzed, and operationalized. But before AI can support mission-critical decisions, it must be tested, validated, and trusted under real operational conditions.</span></i></span></span></span><br><br><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">This is a special opportunity to join us as an Electro-Optical (EO) Imagery Scientist to support the National Geospatial-Intelligence Agency’s (NGA) Assurance and Governance Office (QA) Accreditation of AI Models (AGAIM) program. Looked upon your expertise to help evaluate and validate AI-enabled GEOINT capabilities against operational imagery datasets to ensure AI systems perform reliably in the environments where mission success matters most. Working at the intersection of GEOINT tradecraft, remote sensing science, and AI/ML evaluation. You’ll analyze how environmental effects collection geometry, sensor limitations, and image quality impact algorithm performance to designing analytic methodologies and validation frameworks that test AI systems beyond ideal conditions. Your expertise in EO phenomenology, collection systems, and image exploitation will directly shape how NGA accredits and operationalizes emerging AI capabilities across the enterprise. If you are ready to apply your expertise and directly influence the future of operational AI within national security, apply today!</span></span></span></span><br><br><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><b><span style=\"font-family:Calibri, sans-serif;\">Requirements</span></b></span></span></span><ul style=\"margin-bottom:11px;\"><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Current active Top Secret / SCI clearance with the willingness to obtain CI poly.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">You’ve achieved an accomplishment of a PhD + 10 years / Master's degree + 13 / Bachelor’s degree + 15 / Associate's degree + 16 / 18+ years of relevant experience.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">You’ve gained deep expertise in EO collection systems, phenomenology, and image formation to properly evaluate AI performance as understanding how imagery is created, how sensors behave, and how environmental conditions affect what an algorithm ‘sees’.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Strong experience evaluating AI/ML algorithms using operational EO datasets to support in assessing whether an algorithm performs reliably across the variability complexity of real-world GEOINT collection.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Experience exploiting EO imagery to determine occurrence and location of objects of interest (OOIs), in order to evaluate whether AI outputs are analytically meaningful.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Experience developing, testing, or evaluating analytic methodologies or algorithms to support methodology design, testing framework, and measurable performance standards.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Proficiency with Python, MATLAB, and/or Google Earth Engine as you will be handling large operational datasets, testing analytic workflows, and assessing model outputs.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Deep understanding of remote sensing principles and GEOINT tradecraft.</span></span></span></span></li><li style=\"margin-bottom:11px;margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Experience applying image quality metrics and assessing environmental or sensor impacts in order to understand how haze, shadows, off-nadir angle, weather, compression, or sensor limitations affect algorithm confidence and reliability.</span></span></span></span></li></ul><br><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><b><span style=\"font-family:Calibri, sans-serif;\">Desired</span></b></span></span></span><ul style=\"margin-bottom:11px;\"><li style=\"margin-bottom:11px;margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Experience with computer vision and machine learning applied to EO imagery</span></span></span></span></li></ul><br><br><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">If you are passionate in helping define how NGA evaluates AI performance, establishes operational confidence, and ensures AI-enabled GEOINT capabilities are mission ready before they reach the analysts or the battlefield, send your resume directly to Lanchi Lai, (<a href=\"mailto:[email protected]\" style=\"color:#467886;text-decoration:underline;\">[email protected]</a>).</span></span></span></span><br><br><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><b><i><span style=\"font-family:Calibri, sans-serif;\">At XTS, we believe in taking care of our employees as much as we take care of our clients. As a veteran-owned company, we understand the importance of community, service, and fostering a culture where each team member can thrive. Our commitment to employee well-being is reflected in the comprehensive benefits and growth opportunities we offer. We offer tailored health care plans that fit your lifestyle, along with dental and vision coverage, paid time off (PTO), and a 401K with employer matching to secure your financial future. As we push forward in the rapidly evolving field of AI, XTS is committed to providing employees with tools and opportunities to stay ahead. We are proud to offer our GeoAI scholarship to help our employees further develop their skills and expertise in this innovative field. We take pride in delivering elite workforces to the Intelligence Community, making a real-world impact on critical missions. Join us and experience a company that invests in your success and professional growth.</span></i></b></span></span></span><br> ",
    "description_text": "Artificial intelligence is rapidly changing how GEOINT is collected, analyzed, and operationalized. But before AI can support mission-critical decisions, it must be tested, validated, and trusted under real operational conditions.\n This is a special opportunity to join us as an Electro-Optical (EO) Imagery Scientist to support the National Geospatial-Intelligence Agency’s (NGA) Assurance and Governance Office (QA) Accreditation of AI Models (AGAIM) program. Looked upon your expertise to help evaluate and validate AI-enabled GEOINT capabilities against operational imagery datasets to ensure AI systems perform reliably in the environments where mission success matters most. Working at the intersection of GEOINT tradecraft, remote sensing science, and AI/ML evaluation. You’ll analyze how environmental effects collection geometry, sensor limitations, and image quality impact algorithm performance to designing analytic methodologies and validation frameworks that test AI systems beyond ideal conditions. Your expertise in EO phenomenology, collection systems, and image exploitation will directly shape how NGA accredits and operationalizes emerging AI capabilities across the enterprise. If you are ready to apply your expertise and directly influence the future of operational AI within national security, apply today!\n Requirements Current active Top Secret / SCI clearance with the willingness to obtain CI poly.\n You’ve achieved an accomplishment of a PhD + 10 years / Master's degree + 13 / Bachelor’s degree + 15 / Associate's degree + 16 / 18+ years of relevant experience.\n You’ve gained deep expertise in EO collection systems, phenomenology, and image formation to properly evaluate AI performance as understanding how imagery is created, how sensors behave, and how environmental conditions affect what an algorithm ‘sees’.\n Strong experience evaluating AI/ML algorithms using operational EO datasets to support in assessing whether an algorithm performs reliably across the variability complexity of real-world GEOINT collection.\n Experience exploiting EO imagery to determine occurrence and location of objects of interest (OOIs), in order to evaluate whether AI outputs are analytically meaningful.\n Experience developing, testing, or evaluating analytic methodologies or algorithms to support methodology design, testing framework, and measurable performance standards.\n Proficiency with Python, MATLAB, and/or Google Earth Engine as you will be handling large operational datasets, testing analytic workflows, and assessing model outputs.\n Deep understanding of remote sensing principles and GEOINT tradecraft.\n Experience applying image quality metrics and assessing environmental or sensor impacts in order to understand how haze, shadows, off-nadir angle, weather, compression, or sensor limitations affect algorithm confidence and reliability.\n Desired Experience with computer vision and machine learning applied to EO imagery\n If you are passionate in helping define how NGA evaluates AI performance, establishes operational confidence, and ensures AI-enabled GEOINT capabilities are mission ready before they reach the analysts or the battlefield, send your resume directly to Lanchi Lai, ( [email protected] ).\n At XTS, we believe in taking care of our employees as much as we take care of our clients. As a veteran-owned company, we understand the importance of community, service, and fostering a culture where each team member can thrive. Our commitment to employee well-being is reflected in the comprehensive benefits and growth opportunities we offer. We offer tailored health care plans that fit your lifestyle, along with dental and vision coverage, paid time off (PTO), and a 401K with employer matching to secure your financial future. As we push forward in the rapidly evolving field of AI, XTS is committed to providing employees with tools and opportunities to stay ahead. We are proud to offer our GeoAI scholarship to help our employees further develop their skills and expertise in this innovative field. We take pride in delivering elite workforces to the Intelligence Community, making a real-world impact on critical missions. Join us and experience a company that invests in your success and professional growth.",
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      "title": "Senior Imagery Scientist – EO (TS/SCI)",
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      "datePosted": "2026-05-07",
      "description": "<span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><i><span style=\"font-family:Calibri, sans-serif;\">Artificial intelligence is rapidly changing how GEOINT is collected, analyzed, and operationalized. But before AI can support mission-critical decisions, it must be tested, validated, and trusted under real operational conditions.</span></i></span></span></span><br><br><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">This is a special opportunity to join us as an Electro-Optical (EO) Imagery Scientist to support the National Geospatial-Intelligence Agency’s (NGA) Assurance and Governance Office (QA) Accreditation of AI Models (AGAIM) program. Looked upon your expertise to help evaluate and validate AI-enabled GEOINT capabilities against operational imagery datasets to ensure AI systems perform reliably in the environments where mission success matters most. Working at the intersection of GEOINT tradecraft, remote sensing science, and AI/ML evaluation. You’ll analyze how environmental effects collection geometry, sensor limitations, and image quality impact algorithm performance to designing analytic methodologies and validation frameworks that test AI systems beyond ideal conditions. Your expertise in EO phenomenology, collection systems, and image exploitation will directly shape how NGA accredits and operationalizes emerging AI capabilities across the enterprise. If you are ready to apply your expertise and directly influence the future of operational AI within national security, apply today!</span></span></span></span><br><br><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><b><span style=\"font-family:Calibri, sans-serif;\">Requirements</span></b></span></span></span><ul style=\"margin-bottom:11px;\"><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Current active Top Secret / SCI clearance with the willingness to obtain CI poly.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">You’ve achieved an accomplishment of a PhD + 10 years / Master's degree + 13 / Bachelor’s degree + 15 / Associate's degree + 16 / 18+ years of relevant experience.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">You’ve gained deep expertise in EO collection systems, phenomenology, and image formation to properly evaluate AI performance as understanding how imagery is created, how sensors behave, and how environmental conditions affect what an algorithm ‘sees’.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Strong experience evaluating AI/ML algorithms using operational EO datasets to support in assessing whether an algorithm performs reliably across the variability complexity of real-world GEOINT collection.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Experience exploiting EO imagery to determine occurrence and location of objects of interest (OOIs), in order to evaluate whether AI outputs are analytically meaningful.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Experience developing, testing, or evaluating analytic methodologies or algorithms to support methodology design, testing framework, and measurable performance standards.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Proficiency with Python, MATLAB, and/or Google Earth Engine as you will be handling large operational datasets, testing analytic workflows, and assessing model outputs.</span></span></span></span></li><li style=\"margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Deep understanding of remote sensing principles and GEOINT tradecraft.</span></span></span></span></li><li style=\"margin-bottom:11px;margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Experience applying image quality metrics and assessing environmental or sensor impacts in order to understand how haze, shadows, off-nadir angle, weather, compression, or sensor limitations affect algorithm confidence and reliability.</span></span></span></span></li></ul><br><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><b><span style=\"font-family:Calibri, sans-serif;\">Desired</span></b></span></span></span><ul style=\"margin-bottom:11px;\"><li style=\"margin-bottom:11px;margin-left:8px;\"><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">Experience with computer vision and machine learning applied to EO imagery</span></span></span></span></li></ul><br><br><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><span style=\"font-family:Calibri, sans-serif;\">If you are passionate in helping define how NGA evaluates AI performance, establishes operational confidence, and ensures AI-enabled GEOINT capabilities are mission ready before they reach the analysts or the battlefield, send your resume directly to Lanchi Lai, (<a href=\"mailto:[email protected]\" style=\"color:#467886;text-decoration:underline;\">[email protected]</a>).</span></span></span></span><br><br><span style=\"font-size:12pt;\"><span style=\"line-height:115%;\"><span style=\"font-family:Aptos, sans-serif;\"><b><i><span style=\"font-family:Calibri, sans-serif;\">At XTS, we believe in taking care of our employees as much as we take care of our clients. As a veteran-owned company, we understand the importance of community, service, and fostering a culture where each team member can thrive. Our commitment to employee well-being is reflected in the comprehensive benefits and growth opportunities we offer. We offer tailored health care plans that fit your lifestyle, along with dental and vision coverage, paid time off (PTO), and a 401K with employer matching to secure your financial future. As we push forward in the rapidly evolving field of AI, XTS is committed to providing employees with tools and opportunities to stay ahead. We are proud to offer our GeoAI scholarship to help our employees further develop their skills and expertise in this innovative field. We take pride in delivering elite workforces to the Intelligence Community, making a real-world impact on critical missions. Join us and experience a company that invests in your success and professional growth.</span></i></b></span></span></span><br> ",
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