Contractor Support to Capability Lifecycle AI-ML Engineer

DEFTEC Corporation • Chesapeake, VA

22h

About The Position

This position provides specialized contractor support to the Capability Development Directorate at Headquarters Allied Command Transformation (HQ SACT), focusing on the integration of Artificial Intelligence (AI) and Machine Learning (ML) solutions across the capability lifecycle. The role is responsible for developing and implementing advanced data-driven models and analytics to enhance NATO's capability planning, prioritization, and decision-making processes. Working closely with the CAPDEV Data and Analytics Office (DAO), the AI/ML Engineer will design and optimize algorithms for requirements analysis, capability forecasting, and performance assessment, ensuring alignment with NATO's strategic objectives. Additional responsibilities include supporting data governance, enabling self-service analytics, and contributing to the modernization of capability development through innovative AI/ML applications that improve interoperability, deployability, and sustainability of Alliance forces.

Requirements

• 8+ years of progressive professional experience in data science, advanced analytics, and/or machine learning engineering, including experience delivering operational analytics or decision-support solutions in complex enterprise environments.
• Demonstrated expertise in machine learning and statistical modeling, including development, training, validation, and deployment of models supporting forecasting, risk analysis, performance assessment, or decision support across business or capability lifecycles.
• Demonstrated experience designing and operating automated data pipelines, including ETL/ELT workflows, feature engineering, and data transformation processes to support analytics and Al/ML workloads.
• Demonstrated professional experience with cloud-based analytics and Al/ML platforms, including deployment and operation of models and data pipelines in secure, scalable cloud envi ran men ts.
• Bachelor's degree in Data Science, Computer Science, Mathematics, Engineering, Statistics, or a related quantitative discipline.
• Demonstrated experience integrating Al/ML solutions into enterprise analytics tools, dashboards, or reporting platforms to support operational use by analysts and decision­makers.
• Demonstrated experience with model lifecycle management, including performance monitoring, retraining strategies, version control, documentation, and optimization for production environments.
• Demonstrated experience working within governed or regulated environments, including adherence to data governance, security, and compliance requirements relevant to defense, security, or other highly regulated domains.
• Demonstrated ability to col la borate across multidisciplinary teams, including analysts, data engineers, platform engineers, and system administrators, to deliver interoperable, production-ready analytics solutions.
• Demonstrated ability to communicate complex analytical and Al/ML concepts clearly to both technical and non-technical stakeholders, supporting effective adoption and operational use of delivered solutions. Demonstrated minimum NATO or National SECRET clearance with the appropriate national authority for the duration of the contract.
• Demonstrated proficiency in English as defined in STANAG 6001 (Standardized Linguistic Profile (SLP) 3333 - Listening, Speaking, Reading and Writing) or equivalent.
• Demonstrable proficiency in effective oral and written communication, including briefing and coordinating with business stakeholders.

Responsibilities

• Al/ML Model Development: Design, develop, train, and deploy machine learning models to support forecasting, risk identification, readiness assessment, and decision support across the capability lifecycle.
• Advanced Analytics Integration: Integrate Al/ML models into enterprise analytics workflows, dashboards, and reporting solutions to enable operational use by analysts and decision­makers.
• Data Preparation and Feature Engineering: Develop and maintain data preparation pipelines, feature engineering processes, and training datasets in coordination with data engineering teams to ensure model accuracy, robustness, and traceability.
• Cloud-Based Al/ML Engineering: Implement and operate Al/ML solutions within approved cloud environments, including model training, deployment, and orchestration using secure, scalable architectures.
• Model Lifecycle Management: Establish and execute model validation, performance monitoring, retraining, and version control processes to ensure sustained accuracy and operational relevance of deployed models.
• Responsible Al Practices: Apply responsible and explainable Al principles, including transparency, bias awareness, and interpretability, appropriate to defense and decision support contexts.
• Automation and Optimization: Identify and implement opportunities to automate analytic workflows, model execution, and data processing to improve efficiency and reduce manual intervention.
• Prototyping and Experimentation: Design and deliver proof-of-concept and prototype Al/ML solutions, including exploration of emerging techniques (e.g., large language models or incremental learning), aligned with DAO priorities.
• Performance and Scalability Optimization: Optimize Al/ML pipelines and supporting infrastructure to ensure reliable performance under operational workloads and evolving data volumes.
• Technical Documentation: Produce and maintain comprehensive technical documentation describing Al/ML models, data dependencies, assumptions, limitations, and operational integration points.
• Stakeholder Engagement: Collaborate with analysts, engineers, and stakeholders to translate operational requirements into Al/ML solutions and explain analytic outputs to technical and non-technical audiences.
• Knowledge Transfer: Deliver knowledge transfer, mentoring, and technical guidance to DAO personnel to support long-term sustainment of Al/ML capabilities.
• Security and Compliance: Ensure Al/ML development and deployment comply with NATO and organizational security, data protection, and classification handling requirements.
• Capability Lifecycle Support: Apply Al/ML expertise to support requirements-based planning, capability development, delivery monitoring, and performance assessment activities.
• Continuous Improvement: Identify opportunities to enhance Al/ML methods, tooling, and practices in alignment with DAO's Decision Advantage objectives.
• Technical Support: Provide ongoing technical support and troubleshooting for Al/ML models, pipelines, and integrated analytic solutions.
• Additional Tasks: Perform additional tasks as required by the COTR in scope of this labor category.

Benefits

• DEFTEC offers a comprehensive whole-life benefits package that includes medical, dental, vision, holiday, paid time off, 401K with a match, life insurance, short/long-term disability, and educational reimbursement.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level