AIML Engineer

Spektrum supports apex purchasers (NATO UN EU and National Government and Defence) and their Tier 1 supplier ecosystem with a wide range of specialist services. We provide our clients with professional services specialised aerospace and defence sales delivery and operational subject matter expertise. We are looking for personnel to join our team and support key client projects.

Who we are supporting

Allied Command Transformation (ACT) is NATOs leading agent for change: driving facilitating and advocating the continuous improvement of Alliance capabilities to maintain and enhance the military relevance and effectiveness of the Alliance. The main objectives of ACT are: providing appropriate support to NATO missions and operations; leading NATO military transformation; and improving relationships interaction and practical cooperation with partners nations and international organisations. ACT therefore leads Alliance concept development capability development training and lessons-learned initiatives and provides unfettered military support to policy development within NATO.

The program

Capability Development & Management Support (CDMS)

DCOS Capability Development (CAPDEV) acts as the Supreme Allied Commander Transformations Director for guidance direction and coordination of the activities and resources of the Capability Development Directorate.

The Requirements Division will execute all tasks and activities needed to support requirements management for NATO capabilities

The Capability Requirements (CR) Branch will develop the Capability Requirements Brief and recommended courses of action to resolve issues through the life cycle management of requirements using matrixed cross-functional project-specific Requirements Management teams.

The Requirements Forward Branch (Mons) is responsible for conducting requirements development and management representation and engagement-related functions in Europe.

The Capability Division coordinates the development of capabilities from capability planning through acceptance and then disposal with management entities NATO Headquarters staff and the NATO Governance Structure

The Capability Forward Branch (Mons) coordinates with ACO NCIA NSPA NATO HQ territorial Host Nations and NATO Centres of Excellence (COEs) to support the development of capabilities.

Strategic Plans and Policy (SPP) supports Allied Command Transformation in formalizing military advice to shape future military strategy political guidance and other policy documents supporting NATOs strategic objectives.

Role ID:ACT-CDMS-26-02-B-42

Background

• Deputy Chief of Staff Capability Development (DCOS CAPDEV) acts as the Supreme Allied Commander Transformations Director for guidance direction and co-ordination of the activities and resources of the Capability Development Directorate. CAPDEV is responsible to:
  • Identifyand prioritize Alliance capability development from short to long term ensuring coherence between all capabilities within the CAPDEV portfolio.
  • Lead the determination of required capabilities and prioritization of shortfalls to inform the delivery of materiel and non-materiel solutions across the DoctrineOrganisation Training Material and Leadership Personnel Facilities and Interoperability (DOTMLPFI) lines of effort to enable a holistic approach to capability development ensuring improved interoperabilitydeployabilityand sustainability of Alliance Forces.
• The future Capability Development Directorate will include enduring functionality to effectively plan and managecoherentthrough life capability development aligned to NATOs strategic intent and priorities. The CAPDEV Data and Analytics Office (DAO) is responsible to DCOS for managing the data and platform operations for Capability Lifecycle Requirements and P3M data as well as providing analytics as service and enabling self-service analytics for CAPDEV decision makers.
• As part of ongoingorganisationalfunctional reviews CAPDEV isin the process of implementingmeasures for improved capability development planning and management including the way it collects managesanalysesand reports on capability development and delivery information both legacy and current.

Role Duties and Responsibilities

• 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 andmaintaindata 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 andoperateAI/ML solutions within approved cloud environments including model training deployment and orchestration using secure scalable architectures.

• Model Lifecycle Management:Establishand 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 interpretabilityappropriate todefenceand decision-support contexts.

• Automation and Optimization:Identifyand 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:OptimizeAI/ML pipelines and supporting infrastructure to ensure reliable performance under operational workloads and evolving data volumes.

• Technical Documentation: Produce andmaintaincomprehensive 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 deploymentcomply withNATO and organizational security data protection andclassificationhandling requirements.

• Capability Lifecycle Support: Apply AI/MLexpertiseto support requirements-based planning capability development delivery monitoring and performance assessment activities.

• Continuous Improvement:Identifyopportunities to enhance AI/ML methods tooling and practices in alignment with DAOs Decision Advantageobjectives.

• Technical Support: Provide ongoing technical support and troubleshooting for AI/ML models pipelines and integrated analytic solutions.
• Additional Tasks: Performadditionaltasks as required by Line this labor category.

EssentialSkills and Experience

• 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.

• Demonstratedexpertisein 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.

• Demonstratedexperience designing andoperatingautomated data pipelines including ETL/ELT workflows feature engineering and data transformation processes to support analytics and AI/ML workloads.

• Demonstratedprofessional experience with cloud-based analytics and AI/ML platforms including deployment and operation of models and data pipelines in secure scalable cloud environments.

• Demonstratedexperience integrating AI/ML solutions into enterprise analytics tools dashboards or reporting platforms to support operational use by analysts and decision-makers.

• Demonstratedexperience with model lifecycle management including performance monitoring retraining strategies version control documentation and optimization for production environments.

• Demonstratedexperience working within governed or regulated environments including adherence to data governance security and compliance requirements relevant todefence security or other highly regulated domains.

• Demonstratedability 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.
• Demonstrableproficiencyin effective oral and written communication including briefing and coordinating with business stakeholders.

Education

• Bachelors degree in Data Science Computer Science Mathematics Engineering Statistics ora relatedquantitative discipline.

Language Proficiency

• Advanced Proficiency in English

Working Location

• Norfolk VA USA

Working Policy

• On-Site

Contract Duration

• April2026 December 2030

Security Clearance

• Valid National or NATOSecretpersonal security clearance