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Urgent! LLM Algorithm Research Engineer (Amsterdam) Job Opening In Warsaw – Now Hiring Michael Page

LLM Algorithm Research Engineer (Amsterdam)



Job description

This role is for a Research Engineer specialising in AI systems powered by Large Language Models.

The goal is to design and build multi-agent AI systems, essentially, AI teams that can collaborate, debate, and solve complex problems together.


The engineer will:


  • Develop and test AI agents that can handle reasoning, teamwork, and creativity.

  • Use frameworks like LangChain to develop, test, and deploy AI agents.

  • Improve how agents use knowledge (through tools like RAG - Retrieval Augmented Generation) so they stay accurate and avoid hallucinations

  • Keep up with the latest AI research and bring new ideas into the company.

  • Work with data scientists and engineers to integrate these systems into real products.

  • Measure how well the AI agents work and continuously refine them.





Overall, the role combines research, software development, and applied machine learning, with a strong emphasis on LLMs and agent-based systems.

Growing Research center Team with direct industrial applicationLLM, RAG, Longchain

Education & Background for the Research Engineer LLM :


  • Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or NLP.

  • Strong academic foundation in deep learning, computational linguistics, or applied ML.




Technical ExperienceLLM & Multi-Agent Systems :


  • Direct, hands-on experience in building agents or multi-agent AI systems using Large Language Models (LLMs).

  • Knowledge of agent orchestration frameworks like LangChain or LlamaIndex.

  • Familiarity with agent collaboration methods (debate, cooperative reasoning, creative problem-solving




Programming & Frameworks :


  • Proficiency in Python

  • Experience with ML/DL libraries such as PyTorch or TensorFlow.

  • Skilled in debugging, model prototyping, and performance optimisation





Deep Learning & NLP Knowledge :


  • Strong grasp of Transformers, GPT models, and BERT-like architectures.

  • Understanding of model fine-tuning, transfer learning, and prompt engineering.

  • Familiarity with NLP tasks: information retrieval, summarisation, question-answering.




Data & Knowledge Systems :


  • Experience with vector databases (e.g., Pinecone, Weaviate, FAISS).

  • Knowledge graphs for reasoning and structured data use.

  • Retrieval-Augmented Generation (RAG) techniques to ground LLMs in factual data.




Research & Innovation :


  • Academic publications, conference presentations

  • Ability to evaluate, benchmark, and iteratively optimise AI systems.

Relocation and Visa Sponsorship supported by the client.

Permanent full time contract


Required Skill Profession

Computer Occupations



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