AI Engineer

Slashhash; Den Haag; On-site; EUR 90,000 - 150,000; Full time

Job summary

Slashhash is seeking an AI Engineer for a full-time, on-site role in The Hague, Netherlands. You will build and maintain end-to-end AI/ML pipelines, apply data science techniques, and work with LLMs, RAG, and MLOps in secure environments. NATO SECRET clearance is required.

The role emphasizes developing scalable AI components, collaborating across teams, and delivering reliable, auditable software in secure domains.

Qualifications

• Must-have: strong background in machine learning, data science, and end-to-end AI/ML pipelines.
• Proficient in Python and modern web/API tooling (FastAPI, REST APIs).
• Experience with distributed systems, MLOps, and secure development practices.

Responsibilities

• Apply ML and data science methods to new datasets and evaluate model outcomes.
• Identify and fix issues in ML pipelines, models, and data quality; implement improvements.
• Design, test, document, and maintain moderately complex AI/ML components and scripts.

Skills

Machine Learning

Data Science

AI/ML pipelines

Python

FastAPI

Pydantic

LangChain

LlamaIndex

RAG

Embeddings

Vector databases

LLMs

Generative AI

MLOps

AIOps

CI/CD

REST APIs

Docker

Kubernetes

Helm

Apache Airflow

Argo

SQL

NoSQL

TypeScript

Node.js

Next.js

ETL/ELT

Tools

Docker

Kubernetes

Helm

Apache Airflow

Argo

Job description

AI Engineer required for a full-time on-site contract role in The Hague, Netherlands, supporting NATO. The role involves developing and maintaining end-to-end AI/ML pipelines, applying machine learning and data science techniques, and working with LLMs, RAG, and MLOps in secure environments. Candidates must hold an active NATO SECRET security clearance.

Technical (Must-have)

• Machine Learning
• Data Science
• AI/ML pipelines
• Python
• FastAPI
• Pydantic
• LangChain
• LlamaIndex
• Pydantic AI
• RAG
• Embeddings
• Vector databases
• LLMs
• Generative AI
• MLOps
• AIOps
• CI/CD
• REST APIs
• Docker
• Kubernetes
• Helm
• Apache Airflow
• Argo
• SQL
• NoSQL
• TypeScript
• Node.js
• Next.js
• ETL/ELT

Soft Skills

• Communication
• Collaboration
• Reporting
• Knowledge sharing

Key Responsibilities

• 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

Machine Learning, Data Science, AI/ML pipelines, Python, FastAPI, Pydantic, LangChain, LlamaIndex, Pydantic AI, RAG, Embeddings, Vector databases, LLMs, Generative AI, MLOps, AIOps, CI/CD, REST APIs, Docker, Kubernetes, Helm, Apache Airflow, Argo, SQL, NoSQL, TypeScript, Node.js, Next.js, ETL/ELT