AI Engineer
Role description
About UsLees hieronder meer over de algemene taken die bij deze functie horen, evenals de vereiste vaardigheden.
We'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 Role
We'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
- MLOps, model deployment, and production infrastructure
- AI research applied to real-world/production systems
What You Might Work On
- Designing, 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
- Data Engineers with ML exposure pipelines, ETL/ELT, data infrastructure
- 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
Experience level: Open from strong juniors (1–2 yrs) through senior/lead (10+ yrs). Please specify your seniority and area of specialization in your application or cover note.
Core Skills We're Interested In (any subset)
Programming: Python, SQL, Java, C++, R
Frameworks: PyTorch, TensorFlow, Scikit-learn, HuggingFace Transformers, LangChain/LangGraph, Pandas, NumPy
Data & Infra: ETL/ELT, Data Pipelines, Databricks, Spark, Data Warehousing, Vector Databases (FAISS, Pinecone, Milvus, pgvector).
Other valued experience: Model evaluation/observability (Ragas, Langfuse), red-teaming, A/B experimentation, technical writing, stakeholder communication.
What We Offer
- Competitive, experience-based compensation (open to discussing your expectations).
- Hybrid working model with flexibility.
- Exposure to real, production-scale AI systems not just research. xgiwjmb
- Collaborative team environment across a range of AI specializations.
- Growth path based on demonstrated impact, regardless of formal title coming in.
