As a research engineer, you will work on improving Kapa's ability to answer increasingly complex technical questions. Check out Docker’s documentation for a live example of what Kapa is (look for the “Ask AI” button).
In This Role, You Will
- Work directly with the founding team and our software engineers.
- Research state-of-the-art retrieval and search techniques.
- Deploy machine learning models as part of RAG.
- Continuously improve our quality evaluation frameworks for robust iteration.
- Stay updated with the latest developments in the field and explore their applications.
- Design and run experiments.
You will have support from leading academics in the field, including close advisors such as Douwe Kiela, author of the original RAG paper.
You May Be a Good Fit If You Have
A Master's or PhD degree in Computer Science, Machine Learning, Mathematics, Statistics, or a related field.A thorough understanding of machine learning, deep learning (including LLMs), and natural language processing.Hands-on experience in training, fine-tuning, and deploying large language models.Experience working with vector databases, search indices, or other data stores for search and retrieval applications.Experience building evaluation systems for LLMs or search.Familiarity with information retrieval techniques such as lexical search and dense vector search.The ability to work effectively in a fast-paced environment with sometimes loosely defined tasks.A desire to learn more about machine learning research.This list is neither exhaustive nor mandatory. If you believe you can contribute to Kapa.ai even if you don't meet all these attributes, please reach out.
Seniority
Junior
Employment Type
Full-time
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