You will also help bring machine learning and emerging AI capabilities to these platforms, including information extraction, classification, matching, recommendation, semantic search, RAG, and LLM-based applications. You will explore new ways of connecting scientific information platforms, including technologies such as the Model Context Protocol, with a focus on production systems rather than fundamental ML research.

Your responsibilities

• Develop, maintain, and operate scientific information applications using Python and Django, including APIs, data models, integrations, and data processing workflows.
• Integrate machine learning and AI capabilities into production systems, using technologies such as Large Language Models, retrieval-augmented generation, semantic search, and the Model Context Protocol.
• Evaluate emerging AI technologies and apply them to concrete scientific information use cases.
• Ensure software quality through automated testing, code review, monitoring, and continuous integration.
• Collaborate with software engineers, product owners, and information specialists on technical solutions and architecture.