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Full Stack Engineer with 2+ years in AI & Machine Learning
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 graduate with hands-on experience in full-stack and backend development, specializing in Artificial Intelligence and Machine Learning. Successfully designed and built scalable applications including an interactive Custom Food App and an AI-driven E-Learning Platform with adaptive quizzing. Engineered a real-time Al application combining computer vision and speech-to-text for natural user interaction, and developed a CNN-based system for robust digital image forgery detection. Focused on delivering secure, high-quality software solutions that leverage AI and full-stack capabilities.
JNTUH University College of Engineering, Manthani
Bachelor of Technology · CSE (AI & ML)
September 1, 2021 – June 1, 2025
Sri Chaitanya Junior College
Intermediate Education
September 1, 2019 – May 1, 2021
Manasa School of Excellence
High School
September 1, 2017 – May 1, 2019
GenNextIT
Fullstack Developer
April 1, 2025 – Present
India
WebCooks Software Solutions
Java Developer
July 1, 2024 – Present
India
Smart Board AI -a real-time AI-powered drawing and voice recognition app
June 27, 2026 – Present
Developed a real-time AI application combining computer vision (MediaPipe, OpenCV) for hand gesture recognition with speech-to-text transcription, enabling natural user interaction. Implemented Google Gemini API to analyze handwritten equations drawn on the virtual board and instantly provide solutions and explanations. Designed and deployed a responsive web app interface with Streamlit, integrating live camera feed, dynamic drawing canvas, and real-time voice notes display. Used Python multithreading to handle continuous voice recognition without blocking the main application, and secured API access via environment variables.
Digital Image Forgery Detection Using Deep Learning
June 27, 2026 – Present
Designed and trained a CNN integrated with ELA to detect complex image forgeries such as deepfakes, copy-move, and splicing, achieving high accuracy and robustness. Preprocessed and normalized large-scale image datasets (CASIA v2.0) and applied transformations (rotation, zoom, flipping) to improve the model's generalization and performance. Optimized the system for real-time image analysis, making it suitable for live social media, digital journalism, and legal evidence validation. Integrated the trained model into a user-friendly web interface, demonstrating full-stack development skills and practical deployment of AI solutions.
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in cutting-edge technologies like AI, ML, and computer vision, which indicates a proactive and innovative mindset. The experience in both Java development and MERN stack development shows versatility and a willingness to learn new technologies. The projects also highlight an ability to integrate AI solutions into user-friendly interfaces, suggesting a user-centric approach. The current full-time role as a Fullstack Developer aligns directly with the target role, indicating a clear career path and commitment to the field. The diversity of projects (AI-powered drawing app, image forgery detection, custom food app) suggests adaptability and a broad technical interest.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted problems, suggesting good problem-solving skills. The 'Best Intern' recognition implies a proactive attitude and ability to exceed expectations. The focus on user experience and performance optimization in projects suggests an operational fit for delivering high-quality software solutions. However, without direct assessment data, further evaluation of collaboration, stress handling, and logical reasoning is limited.