JobSphere AI: An Integrated AI-Powered Career Guidance Platform with Multi-Modal Interview Coaching

The rapid evolution of the job market has created a significant gap between candidate skillsets and industry expectations, while existing career guidance systems remain fragmented and static. This paper presents JobSphere AI, an integrated multi-modal career guidance platform that combines resume analysis, adaptive skill assessment, AI-driven interview coaching, and personalized career recommendations within a unified architecture. The system leverages a locally deployed large language model (Llama 3.2 via Ollama) for natural language processing, YOLOv8 [11] for real-time proctoring, and DeepFace [12] for emotion recognition, enabling a comprehensive evaluation of both technical and behavioral competencies. A five-layer modular architecture ensures scalability and seamless integration of heterogeneous AI components. Experimental evaluation on real- world user scenarios demonstrates effective skill extraction (87% accuracy), robust proctoring (91% accuracy), and meaningful career recommendations derived from assessment analytics. The proposed system bridges the gap between academic preparation and industry requirements by providing a continuous, data-driven career development pipeline. The results indicate that multi-modal AI integration significantly enhances the reliability and depth of automated career guidance systems.