Junior AI Engineer

Who are we

At Coinmerce, a Dutch-founded European cryptocurrency platform, we’re on a mission to make cryptocurrency simple, secure, and accessible for everyone. Transparency is our core value, and our open-door policy supports collaboration, innovation, and team spirit in our Schiphol-Rijk office. With over 90 talented colleagues, we’re shaping the future of crypto together—are you ready to join us?

About the role

To expand our quantitative and engineering capabilities, we are looking for an Artificial Intelligence Engineer with a strong foundation in machine learning and data science. As an AI Engineer at Coinmerce, you will play a key role in designing, developing, and deploying AI-driven solutions to improve and automate decision-making processes across our systems. You will work closely with quant researchers, traders, and software engineers to push the boundaries of what is possible.

Responsibilities

• Design, fine-tune, and hyper-optimise LLMs – adapt state-of-the-art models (e.g., GPT-4o, Llama 3, Mistral) with LoRA / QLoRA, PEFT, DeepSpeed, and targeted hyper-parameter tuning.
• Build production-grade RAG pipelines – integrate vector stores (FAISS, Pinecone, Qdrant) with streaming market data to fuel real-time signal generation.
• Deploy low-latency inference on MCP – manage and autoscale GPU endpoints with vLLM.
• Lead frontier research spikes – benchmark and evaluate emerging stacks (LangChain Agents, LlamaIndex, vLLM).
• Collaborate across departments to discover and prioritise business bottlenecks where AI and automation can deliver measurable impact.
• Drive solutions from prototype to production while ensuring robustness, reproducibility, and maintainability.

What you bring:

• 0-2 years building and shipping ML / NLP systems in trading, fintech or other data-driven domains.
• Deep grounding in maths, stats and optimisation; fluent in Python + PyTorch / Hugging Face.
• Hands-on with vector DBs & RAG frameworks (LangChain, LlamaIndex) and modern prompt-engineering tactics.
• Proven track record fine-tuning open-source LLMs (Llama, Mixtral, Mistral).
• Rigorous software-engineering habits: clean code, testing culture, secure SDLC.