Data Scientist/ML Engineer (GEOINT/Computer Vision)

Role Description

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. 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).

Qualifications

• Bachelor's (or equivalent) with 5 - 7 years of experience, or a Master's and 3 to 5 years of experience.
• 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).

Requirements

• 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.).