Research Engineer, Applied AI
Overview
kapa.ai creates enterprise-grade AI assistants from your content.
Job Description
kapa.ai makes it easy for technical companies to build AI support and onboarding bots for their users. Teams at +150 leading startups and enterprises incl. OpenAI, Mixpanel, Mapbox, Docker, Next.js and Prisma use kapa to level up their developer experience and reduce support. We enable companies to use their existing technical knowledge sources incl. docs, tutorials, chat logs, and GitHub issues to generate AI bots that answers developer questions automatically. More than 750k developers have access to kapa.ai via website widgets, Slack/Discord bots, API integrations, or via Zendesk. We’ve been fortunate to be funded by some of the greatest AI investors in Silicon Valley: Initialized Capital (Garry Tan, Alexis Ohanian), Y Combinator, Amjad Masad and Michele Catasta (Replit), and Douwe Kiela (RAG paper author and founder of Contextual AI), and other folks incl. angels at OpenAI.
Responsibilities
- - Work directly with the founding team and our software engineers
- - Work on and do research in state-of-the-art retrieval and search techniques
- - Work on and deploy machine learning models as part of RAG
- - Continuously improve our quality evaluation frameworks to enable robust iteration
- - Keep up with the latest developments in the space and see how they can be applied
- - Design and run experiments
Required Skills
- - 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
About the company
Kapa.ai provides automated answers to developer questions by leveraging technical resources to power an LLM-based chatbot. The platform is designed with a singular focus: delivering the most accurate answers about a product. This system is known as the Answer Engine. Kapa.ai follows a philosophy of Evaluation-Driven Development, recognizing that academic benchmarks and leaderboards have limitations. Aligning AI models requires custom evaluations, and the company’s mission is to help organizations deploy reliable AI assistants capable of addressing technical product questions.
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