TalentArch-AI Claims to Capture

A researcher has developed an autonomous talent acquisition agent called TalentArch-AI, which utilizes a hybrid-search approach to match architectural talent. The system combines BM25 keyword scores with semantic vector similarity to capture both the technical skills and "vibe" of an architect. The agent was tested on a mock dataset of candidates, with a 60/40 weight given to semantic search and keyword matching, respectively. The results showed a tighter selection of candidates compared to a simple keyword filter. The researcher believes that this hybrid approach is the future of recruiting, merging traditional methods with new technologies like embeddings. The experiment was conducted using Python and various libraries, with the code and mock resumes available on GitHub. The researcher's goal is to reduce manual screening and focus on candidates who match both technical and seniority requirements. The project has implications for the HR tech industry, highlighting the potential for domain-specific hybrid AI to improve recruitment processes.