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8 дней назад

OPIR Imagery Scientist

180 000 - 210 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
OPIR Imagery Scientist (OPIR/Infrared Remote Sensing): Developing algorithms, analytic tools, and data-processing pipelines for persistent infrared intelligence exploitation with an accent on sensor phenomenology, data quality, calibration, and uncertainty characterization. Focus on validating AI-assisted workflows, comparing modeled and overhead signatures, and transitioning tools into operational use.

Location: Charlottesville, Virginia, United States; on-site team role

Salary: $180,000–$210,000 USD per year

Company

hirify.global delivers mission and technical expertise for national security and defense challenges, supporting government customers with technology and operational capabilities.

What you will do

  • Exploit OPIR and other EO/IR sensor data to detect, track, and characterize events while separating signatures from clutter and false alarms.
  • Assess processed data, sensor metadata, collection geometry, data quality, calibration, and uncertainty.
  • Design, build, and maintain algorithms, analytic tools, and data-processing pipelines using version control, testing, documentation, and code review.
  • Use agentic AI to accelerate tool development, automate repetitive exploitation and data-conditioning tasks, and prototype analytic methods; verify and validate generated code and outputs.
  • Compare laboratory or modeled signatures with overhead observations and account for sensor response, geometry, atmospheric effects, and background conditions.
  • Support operational transition through testing, verification and validation, documentation, user feedback, collection planning, field tests, and customer collaboration.

Requirements

  • U.S. citizenship and an active TS/SCI clearance, with the ability to obtain a CI polygraph.
  • Hands-on exploitation of OPIR or other infrared sensor data for intelligence production.
  • Working knowledge of IR phenomenology, including sensor resolution, sensitivity, and the strengths and limits of persistent overhead collection.
  • Experience developing analytic tools or data-processing software in Python or a similar language, including Git or comparable version control, testing, and documentation.
  • Proficiency with standard GEOINT and MASINT tools such as ArcGIS, ENVI, SOCET GXP, or RemoteView.

Nice to have

  • Support experience with NGIC, NASIC, NGA, MDA, or another DoD or IC production center; knowledge of TIV, PIV, or AFAST.
  • Degree in physics, engineering, remote sensing, computer science, or another STEM field; graduate education is a plus.
  • Radiometry experience, including radiometric calibration, detector response, signal-to-noise characterization, and uncertainty propagation.
  • Temporal analysis experience, including time-series conditioning, event segmentation, and transient characterization.
  • Experience designing multi-step or tool-using AI agent workflows or evaluating AI performance on analytic tasks.
  • Experience deploying software in classified or air-gapped environments, including containerization, CI/CD, and configuration management.
  • Familiarity with detection theory, signal processing, image processing, or machine learning.
  • Experience with SAR, MSI/HSI, or LiDAR exploitation in addition to IR, or with CONUS/OCONUS test-range collections.

Culture & Benefits

  • Healthcare coverage including medical, dental, and vision, plus a company-contributed Health Savings Account.
  • Annual paid time off, paid holidays, and paid parental leave.
  • 401(k) with a company match and financial wellness support.
  • Training and development opportunities, award programs, and company-sponsored events.
  • Benefits also include family assistance, continued education, and support for work-life balance.
  • Equal opportunity employment and reasonable accommodation support are provided.

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