CONTRACTOR SUPPORT TO CAPABILITY LIFECYCLE AI/ML ENGINEER

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

Taskings

• AI/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 AI/ML models into enterprise analytics workflows, dashboards, and reporting solutions to enable operational use by analysts and decision-makers.
• 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 AI/ML Engineering: Implement and operate AI/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 AI Practices: Apply responsible and explainable AI principles, including transparency, bias awareness, and interpretability, appropriate to defence 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 AI/ML solutions, including exploration of emerging techniques (e.g., large language models or incremental learning), aligned with DAO priorities.
• Performance and Scalability Optimization: Optimize AI/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 AI/ML models, data dependencies, assumptions, limitations, and operational integration points.
• Stakeholder Engagement: Collaborate with analysts, engineers, and stakeholders to translate operational requirements into AI/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 AI/ML capabilities.
• Security and Compliance: Ensure AI/ML development and deployment comply with NATO and organizational security, data protection, and classification handling requirements.
• Capability Lifecycle Support: Apply AI/ML expertise to support requirements-based planning, capability development, delivery monitoring, and performance assessment activities.
• Continuous Improvement: Identify opportunities to enhance AI/ML methods, tooling, and practices in alignment with DAO’s Decision Advantage objectives.
• Technical Support: Provide ongoing technical support and troubleshooting for AI/ML models, pipelines, and integrated analytic solutions.
• Additional Tasks: Perform additional tasks as required by the COTR in scope of this labor category.

• 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 AI/ML workloads.
• Demonstrated professional experience with cloud-based analytics and AI/ML platforms, including deployment and operation of models and data pipelines in secure, scalable cloud environments.
• Bachelor’s degree in Data Science, Computer Science, Mathematics, Engineering, Statistics, or a related quantitative discipline.
• Demonstrated experience integrating AI/ML solutions into enterprise analytics tools, dashboards, or reporting platforms to support operational use by analysts and decision-makers.
• 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 defence , security, or other highly regulated domains.
• Demonstrated ability to collaborate 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 AI/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. VECTOR SYNERGY sp. z o.o., ul. Marcelińska 90, 60-324 Poznań, NIP PL7811857270, REGON 301575740, KRS: 0000369575 Rejestr Przedsiębiorców KRS prowadzony przez Sąd Rejonowy Poznań – Nowe Miasto i Wilda w Poznaniu, VIII Wydział Gospodarczy KRS, kapitał zakładowy wynosi: 73.852,80 złotych wpłacony w całości, TEL +48 616684500, FAX +48 616684501, www.vectorsynergy.com , [email protected]