Join a mission-focused team as a Machine Learning Engineer specializing in computer vision and geospatial intelligence (GEOINT). This role centers on transforming research-developed models into functional, real-world applications using data from the National Geospatial-Intelligence Agency (NGA). You will be responsible for integrating, refining, and validating machine learning algorithms to detect manipulated imagery and video, ensuring performance under operational conditions.
Key Responsibilities
- Design, develop, and deploy machine learning models tailored to image and video analysis, with emphasis on detecting synthetic or altered media
- Process and validate large-scale datasets using robust data cleaning and preprocessing methods
- Implement and evaluate computer vision algorithms derived from technical research papers and prototypes
- Assess model effectiveness using standard metrics including precision, recall, AUC, and localization accuracy
- Optimize models to handle real-world challenges such as compression artifacts, noise, and format inconsistencies
- Operationalize models developed by external research partners within secure, containerized environments
- Use Python-based ML frameworks such as PyTorch and TensorFlow to translate theoretical concepts into production-ready workflows
- Generate clear technical reports, visualizations, and summaries for stakeholder review
- Collaborate with internal teams and external partners during integration, testing, and evaluation phases
- Participate in technical discussions and reviews conducted within secure facilities (SCIF)
Required Qualifications
- Active TS/SCI security clearance and U.S. citizenship
- Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, Physics, Statistics, or a related technical field
- Minimum of 3 years of hands-on experience in machine learning, data science, or computer vision
- Proficiency in Python and experience with ML frameworks including PyTorch and TensorFlow
- Proven ability to work with image and video data formats such as JPG, WEBP, MP4, and AVI
- Experience implementing algorithms from academic or technical publications
- Familiarity with Linux environments, Git version control, and model validation techniques
- Bachelor’s degree with 5–7 years of experience, or Master’s degree with 3–5 years of relevant work history
Preferred Skills
- Background in image forensics, deepfake detection, or geospatial analytics
- Experience supporting Department of Defense or Intelligence Community programs
- Knowledge of Docker or similar containerization tools for deployment and reproducibility
- Exposure to adversarial machine learning, synthetic data generation, or explainable AI
- Ability to bridge theoretical research with practical implementation
- Strong analytical mindset and problem-solving capabilities
- Effective communication skills for engaging both technical and non-technical audiences
- Adaptability in structured, mission-driven settings
Work Environment
This is a full-time, remote position offering flexibility without compromising security or collaboration. The role supports a lean, resourceful team culture focused on delivering high-impact results. All candidates must be comfortable working in classified environments and committed to maintaining rigorous data integrity standards.
