AI Engineer with less than a year in real-world AI applications.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Computer Science Engineering student specialising in Artificial Intelligence and Machine Learning with hands-on experience in building real-world AI applications. Skilled in Python programming, Machine Learning, Deep Learning, and Computer Vision with a strong ability to solve technical problems and develop practical software solutions.
Jawaharlal Nehru Technological University – UCE Wanaparthy
B.Tech · Computer Science Engineering (AI & ML)
August 1, 2022 – June 30, 2026
Sri Chaitanya Junior College, Hyderabad
Intermediate Education (12th Grade)
N/A – Present
St. Joseph's High School
High School (10th Grade)
N/A – Present
Driver Drowsiness Detection System
June 18, 2026 – Present
Developed a real-time driver monitoring system using facial landmark detection. Implemented EAR and MAR algorithms to detect and classify drowsiness conditions. Achieved 95.58% sensitivity and 100% specificity using an SVM classifier. Built a live Streamlit interface with real-time video feedback and automated alert systems.
AI Multi-Modal Healthcare Diagnostic Agent
June 18, 2026 – Present
Built a multi-modal AI system integrating clinical text, medical images, audio, and healthcare records. Implemented CNNs, LSTMs, and Transformer-based attention models for advanced diagnostics. Integrated Explainable AI (XAI) using Grad-CAM and SHAP to provide transparent predictions. Developed an LLM interaction layer supporting voice and text-based clinical queries.
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and initiative in applying AI/ML to real-world problems (healthcare diagnostics, driver safety). This aligns well with an innovative and problem-solving culture. The breadth of technologies used (CNNs, LSTMs, Transformers, SVM, LLMs) indicates a willingness to explore diverse approaches. However, without professional experience or team-based project details, assessing collaboration and adaptability in a corporate environment is limited.
Soft Skills & Operational Fit
The candidate lists problem-solving, team collaboration, analytical thinking, and project management as soft skills. While these are crucial for an AI Engineer, there is no direct evidence from completed tests or work experience to validate their application in a professional setting. The academic projects suggest an ability to manage project scope and solve technical challenges.