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AI Engineer with less than a year in Machine Learning & Python
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Recently graduated B.Tech in Artificial Intelligence and Data Science with hands-on experience in Python, Machine Learning, and data-driven problem solving. Proficient in supervised learning, model evaluation, feature engineering, and data preprocessing using Pandas, NumPy, Matplotlib, and Scikit-learn. Seeking an entry-level ML Engineer or Python Developer role to learn and grow.
Mahendra College of Engineering
B.Tech · Artificial Intelligence and Data Science
August 1, 2022 – June 30, 2026
Saraswathi Matric Hr. Sec. School
12th
June 1, 2021 – May 31, 2021
Saraswathi Matric Hr. Sec. School
10th
June 1, 2020 – May 31, 2020
Livewire
Machine Learning and Python Course
August 1, 2025 – June 1, 2026
India
Crescent Infotech
Full Stack Intern
August 1, 2024 – September 1, 2024
India
NammaPred-Bengaluru-Metro-Intelligence-System
June 27, 2026 – Present
Built an end-to-end Machine Learning pipeline to predict passenger count and crowd levels across Purple, Green, and Yellow BMRCL metro lines using Python and Scikit-learn. Applied six ML algorithms: Linear Regression, Random Forest, XGBoost, Logistic Regression, Random Forest Classifier, and XGBoost Classifier for passenger count and crowd level prediction. Compared six ML models; XGBoost Regressor achieved the highest R2 score of 0.9657, while Random Forest Classifier attained the best classification accuracy of 89.79%.
View ProjectCareHub – Smart Hospital Management & Billing System
June 27, 2026 – Present
Python & MySQL based system to manage patient records and appointments and Automated billing. Automated billing with QR payment and WhatsApp delivery via PyWhatKit, reducing manual effort by ~80%. Designed MySQL relational schema for structured storage of patient, appointment and billing data.
View ProjectFake Instagram Profile Detection using Machine Learning
June 27, 2026 – Present
Built end-to-end ML classification pipeline: data preprocessing, feature engineering, model training and evaluation. Applied supervised learning (Logistic Regression) achieving 94.9% accuracy using Scikit-learn. Analyzed key features like followers/following ratio and profile completeness to distinguish fake accounts.
View ProjectCultural Fit Analysis
The candidate's projects show a strong interest in AI/ML applications, aligning well with an AI Engineer role. The diversity of projects (metro intelligence, fake profile detection, hospital management) indicates a broad curiosity and willingness to apply skills across different domains. The internship experience, though brief, suggests an eagerness to learn and contribute in a professional setting. The focus on practical, problem-solving projects indicates a results-oriented mindset.
Soft Skills & Operational Fit
The candidate demonstrates analytical thinking, problem-solving, and team collaboration skills through project descriptions. The ability to manage end-to-end ML pipelines and automate processes suggests a methodical and efficient operational approach. However, without direct interview data, the depth of these soft skills cannot be fully assessed.