Research Engineer, Applied AI

Kapa makes technical knowledge instantly accessible through AI assistants. As a research engineer you will work on improving Kapa’s ability to answer harder and harder technical questions. Check out Docker’s documentation () for a live example of what Kapa is (look for the “Ask AI” button).

The following challenges should excite you:

• Evaluating a RAG system in production without labelled data.
• Creating your own benchmark from scratch.
• Building an agentic retrieval system that can judge when to be fast and when to take more time.
• Fine tuning embeddings or rerank models.

To solve these challenges you will:

• Work directly with the founding team and our software engineers.
• Keep up with the latest developments in the space and see how they can be applied.
• Design and run experiments.

You may be a good fit if you have:

• A Master's/ PhD degree in Computer Science, Machine Learning, Mathematics, Statistics or a related field.
• A detailed understanding of machine learning, deep learning (including LLMs) and natural language processing.
• Hands-on experience in training, fine-tuning and deploying large language models.
• Have prior experience working with vector databases, search indices, or other data stores for search and retrieval use cases.
• Significant experience building evaluation systems for LLMs or search.
• Familiarity with various information retrieval techniques, such as lexical search and dense vector search.
• The ability to work effectively in a fast in a environment where things are sometimes loosely defined.
• Want to learn more about machine learning research.

* This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to kapa.ai, please reach out.

Location: Remote within Europe. We’re a distributed team and welcome applicants based anywhere in Europe. We also have an office in Copenhagen for those who prefer working on-site or hybrid.