#NC26SED189142 - Machine Learning Engineer
Deadline: June 3, 2026
Requester: NATO
Location: The Hague, Netherlands
Job type: Contractor
Start date: July, 2026
Security clearance: NATO SECRET
SCOPE OF WORK / DUTIES / ROLES
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Apply established machine learning and AI techniques to new problems and datasets;
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Build, optimize, and maintain machine learning and AI models and supporting pipelines;
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Evaluate and monitor ML/AI system outcomes, model performance, and data quality; define appropriate metrics and acceptance criteria;
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Identify issues in models, pipelines, and datasets; recommend and implement improvements;
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Design, develop, test, document, refactor, and maintain moderately complex programs/scripts to support ML development and deployment;
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Follow agreed engineering standards, tools, and best practices to deliver secure, reliable, and maintainable solutions;
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Monitor progress, report status, and communicate risks, blockers, and dependencies in a timely manner;
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Collaborate with teammates through code reviews, design reviews, and shared ownership of deliverables;
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Elicit requirements for ML/AI lifecycle practices, working methods, and automation (e.g., CI/CD, testing, deployment, monitoring);
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Select and implement appropriate lifecycle practices for components and microservices within the ML/AI solution;
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Deploy automation to support well-engineered, repeatable, and secure build/release processes;
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Define ML/AI modules needed for integration builds and produce buIld definitions for each release/generation of the solution;
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Validate and accept completed ML/AI modules against agreed functional, quality, and performance criteria;
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Apply data science techniques to new problems and datasets, using specialized programming approaches where needed;
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Identify and implement opportunities to improve training data, features, and model performance;
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Build and maintain data pipelines using data engineering standards and tools (ETL/ELT);
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Support monitoring of emerging technologies and contribute to internal reports, technology roadmaps, and knowledge sharing.
REQUIRED SKILLS, KNOWLEDGE AND EXPERIENCE
- 5+ years of hands-on experience building ML/AI solutions in Python, with strong foundations in machine learning concepts, software engineering, and production-grade development practices;
- Proven experience designing, developing, optimizing, and maintaining end-to-end AI/ML pipelines (data processing, training, evaluation, deployment, and monitoring);
- Strong track record in model evaluation and performance measurement, including defining metrics, running assessments, and monitoring model qualitY over time;
- Experience applying and adapting pre-trained models (including Generative AI/LLMs) to solve specific business use cases;
- Solid experience with MLOps practices: version control, experiment tracking, model packaging, deployment, monitoring, and automation;
- Proficiency with CI/CD pipelines and DevOps best practices (e.g., Git-based workflows, build/release automation);
- Practical experience with containerization (Docker, Podman) and orchestration using Kubernetes, including infrastructure provisioning and operationalization in cloud environments;
- Experience with workflow orchestration tools such as Apache Airflow and/or Argo Workflows;
- Strong experience building and maintaining REST APIs, ideally for serving ML models and AI services;
- Experience working with SQL and NoSQL databases.
Desirable:
- Experience building production-grade AI agent backends, e.g., using LangChain or pydantic-ai, wrapped in FastAPI services;
- Full-stack experience with TypeScript frameworks such as Next.js;
- Experience working in air-gapped / restricted-network environments.
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