The fastest way to build AI assistants on technical content. Backed by Y Combinator.
About the role
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 ) for a live example of what Kapa is (look for the “Ask AI” button). * 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.
What they're looking for
- 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
More about this role
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 ) for a live example of what Kapa is (look for the “Ask AI” button).
- 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.
- 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.
- 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...
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