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AI Engineer with less than a year in Machine Learning & Deep Learning
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Assessing your cultural and operational fit
AI & ML Engineer with hands-on experience in building machine learning, deep learning, and computer vision models using Python, TensorFlow, Keras, and OpenCV. Skilled in data preprocessing, NLP, and deploying Al solutions with Flask. Experienced through internships and projects in emotion detection and predictive modeling, with strong problem-solving and teamwork abilities.
Hirasugar Institute of Technology
Compueter Science and Engineering
August 1, 2021 – June 30, 2025
Rooman Technologies
AIML Engineeer Intern
September 1, 2024 – February 28, 2025
India
Internship
Android Application Development
October 1, 2022 – November 30, 2022
India
Advanced Real Estate Price Prediction
June 1, 2026 – Present
Developed an ensemble regression model (Random Forest, XGBoost, Gradient Boosting) for accurate property valuation. Applied data preprocessing, feature engineering, and hyperparameter tuning to improve model performance. Achieved 12% higher prediction accuracy compared to baseline Linear Regression
Emotion Detection in Learning Environments
June 1, 2026 – Present
Developed a deep learning model using CNN and OpenCV to recognize students' emotions (happy, sad, confused, attentive) from facial expressions. Integrated the model into a Flask web application for real-time monitoring in virtual classrooms. Achieved ~85-90% accuracy on test datasets, enhancing the potential for personalized learning experiences.
AI Machine Learning Engineer – NSQF Level 5 (NASSCOM NCVET)
NASSCOM NCVET
June 1, 2026 – Present
Artificial Intelligence
Elewayte
December 1, 2023 – January 1, 2024
Data Structures and Algorithms
Coursera
December 1, 2023 – Present
Android Application Development Internship
College
October 26, 2023 – November 25, 2023
Core Java Programming
Infosys Springboard
June 1, 2023 – Present
Cultural Fit Analysis
The candidate shows a strong interest in AI/ML through academic projects, an AIML Engineer internship, and relevant certifications. The diversity of projects (emotion detection, real estate prediction) and exposure to different ML algorithms (CNN, RNN, ensemble models) indicates a broad learning appetite. The Android development internship, while not directly AI-related, shows versatility and a willingness to explore different technical domains. This aligns with a culture that values continuous learning and adaptability.
Soft Skills & Operational Fit
The candidate's profile summary mentions strong problem-solving and teamwork abilities. Project descriptions indicate an ability to work on complex technical challenges and deliver measurable improvements (e.g., 85-90% accuracy, 12% higher prediction accuracy). The internship experience suggests an ability to integrate into a professional environment and apply learned skills.