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Entry-level AI & Full-Stack Engineer with Generative AI and Deep Learning expertise
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI & Full-Stack Engineer with expertise in Generative AI, Deep Learning, and LLMs. Skilled in building and deploying scalable web applications and optimized ML models utilizing Python, FastAPI, React, Next.js, and LangChain.
Holy Grace Academy Of Engineering, APJ Abdul Kalam Technological University
Bachelor of Technology · Computer Science and Engineering
N/A – June 30, 2025
Zoople Technologies
AI Engineering Intern
July 1, 2025 – August 1, 2025
Cochin, Kerala, India
Facial Emotion Recognition System
June 28, 2026 – Present
Engineered a custom CNN for emotion recognition using Python, TensorFlow, and Keras, achieving 99.11% accuracy and 100% test precision. Optimized data preprocessing and inference pipelines with OpenCV and NumPy, successfully deploying a performant 3.6M parameter model.
Wine Quality Predictive Analytics
June 28, 2026 – Present
Developed a live wine quality prediction web app using Python, Streamlit, and XGBoost, deploying a secure and robust data preprocessing pipeline. Optimized model performance using SMOTE and RandomizedSearchCV to resolve class imbalance, achieving 92% Accuracy and 93% AUC-ROC.
Cultural Fit Analysis
The candidate's projects demonstrate initiative and a passion for AI/ML, which aligns well with an AI Engineer role. The diversity of projects (emotion recognition, wine quality prediction, generative AI agent) shows a broad interest within the AI domain. However, the limited professional experience (one internship) and lack of explicit team collaboration details make a comprehensive cultural fit assessment challenging. The candidate is still pursuing their bachelor's degree, indicating a potential need for mentorship and structured guidance.
Soft Skills & Operational Fit
The candidate's resume highlights strong technical skills in AI/ML and full-stack development. The descriptions of projects and internship indicate an ability to tackle complex problems, optimize performance, and deliver user-centric solutions. However, without specific soft skill assessments or team-based project details, it's difficult to fully assess operational fit beyond technical contributions.