> Markdown version of [/jobs/ext/1365498-ai-scientist-ai-retrieval-systems](https://www.wearedevelopers.com/jobs/ext/1365498-ai-scientist-ai-retrieval-systems). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Scientist - AI Retrieval Systems - **Company:** Cataluña - **Location:** Barcelona, Spain (Remote available) - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Automated Storage and Retrieval Systems, Graph Database, Python (Programming Language), Machine Learning, Neo4j, Large Language Models, Deep Learning, Information Technology - **Published:** July 21, 2026 - **Apply:** https://www.adzuna.es/contact-us.html ## About the Role PhD degree in Data Science, Computer Science, Information Technology, Artificial Intelligence, Physics or related field 1-2 years of experience, preferably in a mathematical, engineering, scientific, or technical setting. Relevant experience in knowledge graphs and retrieval systems Strong communication skills Ability to collaborate effectively within a multidisciplinary and multicultural environment Curiosity, and a proactive, solution-oriented mindset Excitement to work in a dynamic and fast-paced environment, ability to thrives in ambiguity Technical skills Proficiency in Python Understanding of fundamental computer science principles Solid understanding of machine learning principles and architectures Fundamentals of statistics Excellent research and analytical skills Experience in ontology engineering and semantic modeling Experience in designing and developing RAG systems Familiarity with Neo4j Contributions to research (publications in top-tier conferences) or open-source projects Nice to have: Proven excellence in relevant areas (e.g., awards, competition wins) Proven ability to independently solve complex problems or lead challenging projects Academic or practical background in physics or other natural sciences / engineering Experience with good coding practices and software development standards Proficiency in agentic and deep learning frameworks Hands-on experience with large language models and/or other state of the art models ## Description As an AI Scientist specialized in retrieval systems and knowledge graphs, you will play a key role in developing Axiomatic's verifiable scientific reasoning. Your responsibilities will include designing, prototyping, developing, testing and iterating on the core architecture. You will also manage data curation, conduct benchmarking to evaluate performance, analyze reasoning flaws and propose solutions. Close collaboration with our focused cross-functional team, consisting of AI Engineers, Software Engineers, Physicists and AI scientists, and regular alignment of the development with the customer and business needs will be essential to the success of the project. Your mission: AI Research and Development: Contribute to the development of validated AI reasoning models and architectures, focusing on automated reasoning techniques and application to scientific fields where rigour and reliability are fundamental Data & Benchmarking: Supervise dataset curation, run benchmarks, and analyze performance results to guide improvements. Collaboration: Work closely with a cross-functional team of engineers and scientists, collaborating on solving challenging problems at the intersection of AI, physics and engineering. Documentation and Reporting: Develop detailed technical documentation and present research findings to internal teams and external stakeholders. Research & Publication: Contribute to cutting-edge research and publish results in top AI conferences and journals, helping advance the global AI research community whenever opportunities arise. ## Related Videos - [Graphs and RAGs Everywhere... But What Are They? - Andreas Kollegger - Neo4j](https://www.wearedevelopers.com/videos/1311-graphs-and-rags-everywhere-but-what-are-they-andreas-kollegger-neo4j) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Knowledge graph based chatbot](https://www.wearedevelopers.com/videos/754-knowledge-graph-based-chatbot) - [Cyber Sleuth: Finding Hidden Connections in Cyber Data](https://www.wearedevelopers.com/videos/893-cyber-sleuth-finding-hidden-connections-in-cyber-data) - [Give Your LLMs a Left Brain](https://www.wearedevelopers.com/videos/1160-give-your-llms-a-left-brain) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)