AI Engineer Netherlands (Hybrid)Location: NetherlandsWork model: Hybrid (flexible 1–3 days/week on-site)Type: Full-time (Contract options also considered)Level: Open to Junior, Mid, Senior, and Lead please indicate your level when applyingTeam: AI / Machine Learning / Data

About UsWe're building AI-driven products and systems, and are growing our AI engineering team in the Netherlands. We're casting a wide net across the AI/ML/Data ecosystem from applied ML engineers to LLM/GenAI specialists to MLOps and AI infrastructure experts because we want to understand the full range of talent and experience available in the market before we finalize our hiring plan.

Whatever your specialization within AI, we'd like to hear from you.

• The RoleWe're looking for AI Engineers across the full spectrum of AI/ML work, including (but not limited to):Machine learning & deep learning model development
• Generative AI, LLMs, RAG, and multi-agent systems
• NLP, computer vision, and predictive modelling
• Data engineering & ML pipelines (ETL/ELT, feature engineering)
• MLOps, model deployment, and production infrastructure
• AI research applied to real-world/production systems
• AI in specialized domains (fintech, healthcare, industrial, EdTech, cybersecurity, robotics, etc.)

• What You Might Work OnDesigning, training, and evaluating ML/DL models for real product use cases
• Building and deploying LLM-powered applications (RAG, agents, fine-tuning, prompt engineering)
• Building data pipelines and infrastructure to support ML systems at scale
• Taking models from research/prototype to production (optimization, latency, reliability)
• Applying MLOps practices CI/CD, containerization, monitoring, versioning
• Collaborating with product, data, and engineering teams to translate business needs into AI solutions
• Evaluating models, running experiments, and improving performance based on data

Who We Want to Hear From

• We welcome applications from a wide range of backgrounds, including:AI/ML Engineers model development, deployment, and production ML
• Generative AI / LLM Engineers RAG, agents, fine-tuning, prompt engineering
• Data Engineers with ML exposure pipelines, ETL/ELT, data infrastructure
• MLOps / AI Infrastructure Engineers deployment, monitoring, cloud/infra
• AI Researchers with applied/production experience
• Computer Vision / NLP specialists
• Technical AI educators / course developers (if you also train or mentor others)
• Candidates from adjacent fields (software engineering, data science) with strong AI/ML exposure
•