Job Requirements
Reston, VA
Top Secret/SCI Polygraph not specified
Mid Level Career (5+ yrs experience)
$150,000 - $250,000
Job Description
Position: TS/SCI AI/ML Engineer (Imagery)
Clearance Level: TS/SCI
US Citizenship: Required
Job Classification: Regular, Full-Time
Location: Reston, VA
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:
Our client is looking for a Data Scientist/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 with detection of AI-generated and manipulated imagery, or introduction of pattern recognition for imagery. 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. The 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 into operational workflows.
Integrate and operationalize machine learning and computer vision models developed by research partners
Apply algorithms to datasets and generate results aligned with project 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 stakeholders
Collaborate with internal teams and external partners to support integration and testing
Participate in technical meetings and reviews within secure environments. Candidates must have 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.
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
Experience with image forensics, alteration detection, or related analytics
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 working in classified environments
Familiarity with containerization (Docker) and deployment pipelines
Experience handling large-scale or multi-format datasets (JPG, WEBP, MP4, AVI)
Knowledge of 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.
Clearance Level: TS/SCI
US Citizenship: Required
Job Classification: Regular, Full-Time
Location: Reston, VA
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:
Our client is looking for a Data Scientist/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 with detection of AI-generated and manipulated imagery, or introduction of pattern recognition for imagery. 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. The 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 into operational workflows.
Integrate and operationalize machine learning and computer vision models developed by research partners
Apply algorithms to datasets and generate results aligned with project 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 stakeholders
Collaborate with internal teams and external partners to support integration and testing
Participate in technical meetings and reviews within secure environments. Candidates must have 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.
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
Experience with image forensics, alteration detection, or related analytics
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 working in classified environments
Familiarity with containerization (Docker) and deployment pipelines
Experience handling large-scale or multi-format datasets (JPG, WEBP, MP4, AVI)
Knowledge of 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.
group id: 10112344
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