Research Engineer, Applied AI

We make it easy for developer-facing companies to build AI support bots for their community. Teams at OpenAI, Airbyte and NextJS use kapa.ai to help onboard new users and reduce support. Sign up at: https://www.kapa.ai/

Location: Remote
Company size: 10–50
Posted: 2mo ago
Via: Yc

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Job listing · Updated 21 AUG 2026

Research Engineer, Applied AI

Kapa.ai· GB / DE / FR / NO / DK / SE / FI / PT / ES / BE / NL / IT / CH / AT / CZ / PL / EE / LV / LT / SK / HU / SI / HR / RU / UA / Remote (GB; DE; FR; NO; DK; SE; FI; PT; ES; BE; NL; IT; CH; AT; CZ; PL; EE; LV; LT; SK; HU; SI; HR; RU; UA)View company profile

Job title: Research Engineer, Applied AI
Job location: GB / DE / FR / NO / DK / SE / FI / PT / ES / BE / NL / IT / CH / AT / CZ / PL / EE / LV / LT / SK / HU / SI / HR / RU / UA / Remote (GB; DE; FR; NO; DK; SE; FI; PT; ES; BE; NL; IT; CH; AT; CZ; PL; EE; LV; LT; SK; HU; SI; HR; RU; UA)
Job listing URL: https://www.ycombinator.com/companies/kapa-ai/jobs/huRVu7n-research-engineer-applied-ai
Job description: 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 ([https://docs.docker.com](https://docs.docker.com/)) 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.

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