Whitetable.ai
|Founding Engineer
Summary
Led the development of a hiring intelligence incoporating latest research in multi-agent AI systems, with streamlined deployment and iteration using Jenkins and Docker. Designed an adaptable orchestration system, dynamically overseeing a multitude of 20+ diverse agents in real-time, and optimizing 100s interview scenarios with a staggering 90% automation proficiency. Enhanced generation accuracy and reduced hallucination errors by 30% through the integration of ReAct agents and advanced retriever tools, surpassing the capabilities of conventional LLM chains.
Highlights
Fine-tuned the Gemini Flash model for resume parsing, improving the model's ability to extract and structure candidate information for job-matching scenarios.
Delivering a Critical AI System Under Tight Timelines
Built a custom ReAct agent with controlled prompting and parameter tuning to stabilize the results.
Integrated KSA (Knowledge, Skills, Abilities) framework, and integrated it into algorithm, ensuring it accurately reflected the true candidate-job fit.
The system was successfully launched on time, now screening 100s of candidates daily. It has become one of Whitetable.ai's most impactful tool, significantly improving the hiring process.