Summary
✨ AI‑Generated
Work as an AI Engineer on applied machine learning and data science problems, evaluating models, datasets, pipelines, and data quality. You will design, develop, test, document, refactor, and maintain AI/ML components while applying secure engineering standards. The role spans requirements, automation, deployment, monitoring, integration, and lifecycle engineering in a fully onsite environment.
Highlights
Negotiable start date, work on applied AI and machine learning challenges, exposure to the full AI/software lifecycle, and strong emphasis on engineering quality, security, automation, and maintainability.
Description
Start date: Negotiable
Clearance: NATO Secret
Location: The Hague (100% onsite)
Duties & Role:
Apply machine learning and data science techniques to new problems and datasets, including evaluating model outcomes, performance, and data quality.
Identify issues in machine learning systems, models, pipelines, datasets, and development activities, and implement practical improvements.
Design, develop, test, document, amend, refactor, and maintain moderately complex programs, scripts, and AI/ML components.
Apply agreed engineering standards, tools, and secure development practices to deliver reliable, maintainable, and well-engineered solutions.
Support AI/software lifecycle engineering by eliciting requirements, selecting suitable working practices, and deploying automation for development, testing, release, deployment, and monitoring.
Define AI modules for integration builds, produce build definitions, and validate completed modules against agreed functional, quality, security, and performance criteria.
Build, maintain, and improve data pipelines using data engineering standards and tools, including ETL/ELT processes.
Monitor progress, report status, communicate risks or blockers, and collaborate with colleagues through reviews and shared delivery ownership.
Support monitoring of emerging technologies, contribute to technology assessments, reports, roadmaps, and knowledge sharing.
Requirements
Skills, Knowledge & Experience:
The candidate must have a currently active NATO SECRET security clearance Experience developing, optimising, deploying, and maintaining end-to-end AI/ML pipelines, including training, packaging, monitoring, and lifecycle management.
Strong hands-on experience in programming, machine learning, software engineering, and applied AI development.
Solid understanding of machine learning concepts, model evaluation, performance measurement, assessment methods, and model improvement techniques.
Experience applying pre-trained models, foundation models, LLMs, and Generative AI to practical use cases.
Experience with RAG, embeddings, vector databases, AI application architectures, and production-grade AI agent backends using frameworks such as LangChain, LlamaIndex, Pydantic AI, or similar.
Strong experience with MLOps/AIOps, version control, CI/CD, automation, experiment/model lifecycle practices, and build/release workflows.
Experience developing REST APIs, backend services, and modern Python applications using FastAPI, Pydantic, or similar frameworks.
Experience with containerisation, orchestration, and deployment technologies including Docker, Kubernetes, Helm, cloud infrastructure provisioning, and workflow orchestration tools such as Airflow or Argo.
Experience implementing guardrails, observability, logging, monitoring, and operational controls for LLM-based systems.
Experience working with SQL and NoSQL databases.
Experience with TypeScript, Node.js, or frontend frameworks such as Next.js.
Experience working in secure, restricted, or air-gapped environments
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