AI/ML Engineer

Position: Capability Lifecycle AI/ML Engineer

Location: Norfolk, VA, USA (On-site)

Duration: 4 years

Responsibilities:

• Design, develop, train, and deploy AI/ML models to support forecasting, risk assessment, readiness evaluation, and decision support across the capability lifecycle.
• Integrate AI/ML models into enterprise analytics workflows, dashboards, and reporting solutions for operational use.
• Develop and maintain data preparation pipelines, feature engineering processes, and training datasets in coordination with data engineering teams.
• Implement AI/ML solutions in secure, scalable cloud environments, including model orchestration and deployment.
• Establish model lifecycle management processes, including validation, performance monitoring, retraining, and version control.
• Apply responsible and explainable AI principles (transparency, bias awareness, interpretability) in decision-support contexts.
• Automate analytic workflows, model execution, and data processing to improve efficiency.
• Prototype and experiment with AI/ML solutions, including exploration of emerging techniques (e.g., large language models, incremental learning).
• Optimize AI/ML pipelines for performance and scalability under operational workloads.
• Produce and maintain technical documentation for models, data dependencies, assumptions, limitations, and integration points.
• Collaborate with analysts, engineers, and stakeholders to translate operational requirements into AI/ML solutions.
• Deliver knowledge transfer, mentoring, and technical guidance to support long-term sustainment of AI/ML capabilities.
• Ensure AI/ML development and deployment comply with security, data protection, and regulatory requirements.
• Support capability lifecycle activities including planning, development, monitoring, and performance assessment.
• Provide ongoing technical support and troubleshooting for AI/ML models and integrated analytics solutions.

Essential Qualifications:

• 8+ years of experience in data science, advanced analytics, or machine learning engineering, including operational or enterprise decision-support applications.
• Expertise in ML/statistical modeling, including development, training, validation, and deployment of models for forecasting, risk analysis, or performance assessment.
• Experience designing and operating automated data pipelines, feature engineering, and ETL/ELT workflows.
• Experience with cloud-based AI/ML platforms in secure, regulated, or enterprise environments.
• Bachelor s degree in Data Science, Computer Science, Mathematics, Engineering, Statistics, or related quantitative discipline.
• Experience integrating AI/ML outputs into dashboards, analytics platforms, or reporting tools.
• Experience with model lifecycle management: performance monitoring, retraining, version control, and documentation.
• Experience working in governed or regulated environments, with strong adherence to security and compliance requirements.
• Ability to collaborate with multidisciplinary teams and communicate technical concepts clearly to technical and non-technical stakeholders.
• Active security clearance (NATO or National SECRET) required.
• Proficiency in English (STANAG 6001 SLP 3333 or equivalent).

Skills & Experience:

• 8+ years in data science or ML engineering; 5+ years developing and deploying operational or enterprise AI/ML models.
• 8+ years professional experience, including 5+ years deploying AI/ML models in production with full lifecycle management.
• 6+ years professional experience, including 3+ years designing and operating automated data pipelines and feature engineering workflows.
• 6+ years professional experience, including 3+ years implementing AI/ML solutions on secure cloud platforms.
• 5+ years professional experience, including 2+ years integrating AI/ML outputs into operational analytics platforms.
• 5+ years professional experience, including 2+ years applying responsible AI practices, governance, documentation, and explainability.
• Bachelor s degree in Computer Science, Data Science, Information Systems, or related field.
• Effective oral and written communication skills, including briefing and coordinating with stakeholders.