Data Scientist / ML Engineer (GEOINT / Computer Vision) VAWFH 1646 Job at Global
Global InfoTek, Inc, Reston, VA, United States
Clearance Level: TS/SCI
US Citizenship: Required
Job Classification: Regular, Full-Time
Location: Remote
Years of Experience: 5-7 Years
Education Level: Bachelor degree or Master’s degree is required in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields.
Briefly Describe the Work: GITI is looking for a Machine Learning (ML) Engineer with documented expertise to be responsible for researching, developing, architecting, and integrating ML models, algorithms, tools, and techniques into existing or new environments. A candidate who has experience analyzing large datasets with preprocessing data skills, data cleansing, and conducting data integrity and validation actions. A candidate who will design, develop, and integrate ML models and algorithms to address specific problems, such as detection of AI-generated and manipulated imagery and video, etc., and introduce ML and pattern recognition to discover hidden insights. Successful candidates for this role must have critical thinking skills, be creative, curious, resourceful, and have a passion for conveying a wide range of information through research leading to deeper insights. The candidate may work independently but participate in project-wide reviews of requirements, system architecture, and detailed design documents. An ML Engineer must be able to collaborate well with a strong lean-forward attitude to shift knowledge left, deliver well, and produce quality results. The selected candidate will play a critical role in bridging research and operations, integrating advanced algorithms developed by academic partners into operational workflows using NGA data and environments.
Integrate and operationalize machine learning and computer vision models developed by research partners
Apply delivered algorithms to NGA-provided datasets and generate results aligned with program requirements
Evaluate model performance using metrics such as accuracy, precision, recall, ROC/AUC, and localization quality
Adapt and optimize models for real-world conditions (compression, noise, format variability)
Work with containerized solutions (Docker or similar) to support deployment and reproducibility
Translate research concepts, theory, and technical reports into practical implementations and workflows
Generate technical reports, visualizations, and summaries suitable for NGA stakeholders
Collaborate with internal teams and external partners to support integration and testing
Participate in technical meetings and reviews within secure environments (SCIF)
Career level with a complete understanding and wide application of technical principles, theories and concepts. Working under only general direction, provides technical solutions to a wide range of difficult problems. Independently determines and develops approach to solutions. Bachelor's (or equivalent) with 5 - 7 years of experience, or a Master's and 3 to 5 years of experience.
Required Skills:
3+ years of experience in machine learning / computer vision / data science
Strong proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow)
Experience working with image and/or video data
Ability to understand and implement research-level algorithms from technical papers and reports
Experience with model evaluation, validation, and performance analysis
Familiarity with Linux-based environments and version control systems (e.g., Git)
Desired Skills:
Experience with image forensics, deepfake detection, or GEOINT-related analytics
Experience working with DoD / IC programs or classified environments
Familiarity with containerization (Docker) and deployment pipelines
Experience handling large-scale or multi-format datasets (JPG, WEBP, MP4, AVI)
Knowledge of adversarial robustness, synthetic data generation, or explainable AI
Ability to bridge theory and implementation
Strong problem-solving and analytical skills
Effective communication with both technical and non-technical stakeholders
Comfortable working in structured, mission-driven environments
Relevant Certifications:
Certifications in machine learning, data science, or related fields (e.g., TensorFlow Developer Certificate, AWS Certified Machine Learning Specialty, IBM Machine Learning Professional Certificate, Google Professional Machine Learning Engineer Certification, IABAC: Certified Machine Learning Expert Certification, etc.
Global InfoTek, Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or based on disability.
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US Citizenship: Required
Job Classification: Regular, Full-Time
Location: Remote
Years of Experience: 5-7 Years
Education Level: Bachelor degree or Master’s degree is required in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields.
Briefly Describe the Work: GITI is looking for a Machine Learning (ML) Engineer with documented expertise to be responsible for researching, developing, architecting, and integrating ML models, algorithms, tools, and techniques into existing or new environments. A candidate who has experience analyzing large datasets with preprocessing data skills, data cleansing, and conducting data integrity and validation actions. A candidate who will design, develop, and integrate ML models and algorithms to address specific problems, such as detection of AI-generated and manipulated imagery and video, etc., and introduce ML and pattern recognition to discover hidden insights. Successful candidates for this role must have critical thinking skills, be creative, curious, resourceful, and have a passion for conveying a wide range of information through research leading to deeper insights. The candidate may work independently but participate in project-wide reviews of requirements, system architecture, and detailed design documents. An ML Engineer must be able to collaborate well with a strong lean-forward attitude to shift knowledge left, deliver well, and produce quality results. The selected candidate will play a critical role in bridging research and operations, integrating advanced algorithms developed by academic partners into operational workflows using NGA data and environments.
Integrate and operationalize machine learning and computer vision models developed by research partners
Apply delivered algorithms to NGA-provided datasets and generate results aligned with program requirements
Evaluate model performance using metrics such as accuracy, precision, recall, ROC/AUC, and localization quality
Adapt and optimize models for real-world conditions (compression, noise, format variability)
Work with containerized solutions (Docker or similar) to support deployment and reproducibility
Translate research concepts, theory, and technical reports into practical implementations and workflows
Generate technical reports, visualizations, and summaries suitable for NGA stakeholders
Collaborate with internal teams and external partners to support integration and testing
Participate in technical meetings and reviews within secure environments (SCIF)
Career level with a complete understanding and wide application of technical principles, theories and concepts. Working under only general direction, provides technical solutions to a wide range of difficult problems. Independently determines and develops approach to solutions. Bachelor's (or equivalent) with 5 - 7 years of experience, or a Master's and 3 to 5 years of experience.
Required Skills:
3+ years of experience in machine learning / computer vision / data science
Strong proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow)
Experience working with image and/or video data
Ability to understand and implement research-level algorithms from technical papers and reports
Experience with model evaluation, validation, and performance analysis
Familiarity with Linux-based environments and version control systems (e.g., Git)
Desired Skills:
Experience with image forensics, deepfake detection, or GEOINT-related analytics
Experience working with DoD / IC programs or classified environments
Familiarity with containerization (Docker) and deployment pipelines
Experience handling large-scale or multi-format datasets (JPG, WEBP, MP4, AVI)
Knowledge of adversarial robustness, synthetic data generation, or explainable AI
Ability to bridge theory and implementation
Strong problem-solving and analytical skills
Effective communication with both technical and non-technical stakeholders
Comfortable working in structured, mission-driven environments
Relevant Certifications:
Certifications in machine learning, data science, or related fields (e.g., TensorFlow Developer Certificate, AWS Certified Machine Learning Specialty, IBM Machine Learning Professional Certificate, Google Professional Machine Learning Engineer Certification, IABAC: Certified Machine Learning Expert Certification, etc.
Global InfoTek, Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or based on disability.
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