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Imagery Scientist - EO Senior-Job#780 at Allen Integrated Solutions

Springfield, Virginia, United States -

Full Time

Start Date

Immediate

Expiry Date

02 Aug, 26

Salary

0.0

Posted On

04 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

EO imagery, Remote sensing, Image formation process, Exploitation products, Imagery quality metrics, Sensor metadata, OOI location, Phenomenology, Computer vision, Machine learning, Data analysis, Technical communication

Industry

Defense and Space Manufacturing

Description

Imagery Scientist - EO Senior Location: Springfield, VA / Washington Metro Area TS/SCI REQUIRED/Current CI Poly or Willing to take one Required Allen Integrated Solutions is supporting NGA's Assurance and Governance Office (QA) Accreditation of AI Models (AGAIM) program. This position will identify and acquire imagery in support of Level 3 Accreditation—the application of the AI algorithm to operational imagery data sets. This position will serve as experts in your respective image modality and prepare imagery of the necessary quality, standards, and requirements. You will develop solutions that are informed by the specific phenomenology limitations and advantages of the sensors and platforms. Required Experience/Skills: 4+ years as an EO expert with understanding of collection, phenomenology, image formation process, and exploitation products Experience with EO imagery quality metrics and sensor metadata Experience exploiting EO to determine the occurrence and location of an OOI Experience communicating with technical and non-technical audiences about the availability and capabilities of EO Exhibit an understanding of the principles of remote sensing and imagery processing and advanced exploitation methods Desired Experience applying CV and machine learning to EO imagery

Responsibilities

The Imagery Scientist will identify and acquire imagery to support the accreditation of AI models for operational data sets. They will serve as experts in image modality and develop solutions based on sensor phenomenology and platform limitations.