AI Engineer with less than a year in Machine Learning & Data Science
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Detail-oriented Artificial Intelligence & Data Science Engineer with strong foundation in Machine Learning, Data Analytics, Python, and Computer Vision. Experienced in building end-to-end AI/ML projects, data pipelines, dashboards, and predictive models. Passionate about solving real-world problems using data-driven and AI-based solutions. Seeking an AI/ML Engineer role.
SNJB's KBJ COE Chandwad
B.E. · Artificial Intelligence and Data Science
August 1, 2021 – June 30, 2025
Python Full Stack Development with Data Analytics & Machine Learning
Internship
June 1, 2025 – April 1, 2026
India
Weather Classification using Machine Learning
June 1, 2026 – Present
Built a classification model to predict weather conditions (Rainy, Sunny, Cloudy). Performed data preprocessing, encoding, scaling, and feature selection. Applied ML algorithms to improve prediction accuracy and model performance.
Super Store Sales Dashboard
June 1, 2026 – Present
Designed interactive Power BI dashboard for sales and profit analysis. Built KPI reports for revenue, profit margin, and customer segmentation. Enabled data-driven decision-making using visualization insights.
Smart Ticket Booking System
June 1, 2026 – Present
Designed and managed relational database for booking system. Used advanced SQL queries, joins, and data handling operations.
Enhanced Surveillance System using Deep Learning
June 1, 2026 – Present
Developed a real-time violence detection system using MobileNetV2 CNN model. Optimized model using TensorFlow Lite for deployment on edge device (Raspberry Pi). Implemented real-time video processing using OpenCV. Designed automated alert system using SMTP notifications.
Google Foundations of Data Science
June 1, 2026 – Present
NPTEL - Python for Data Science
NPTEL
June 1, 2026 – Present
Research Project Competition (AAVISHKAR)
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and internship show a strong interest in AI/ML and data science, aligning well with an AI Engineer role. The diversity of projects, from deep learning surveillance to sales dashboards and database systems, indicates a broad technical curiosity and willingness to explore different problem domains. The certifications further demonstrate a commitment to continuous learning, which is a positive cultural indicator. However, the candidate's experience is primarily academic and internship-based, which might require mentorship in a fast-paced industry environment.
Soft Skills & Operational Fit
The candidate demonstrates a proactive learning attitude through certifications and academic projects. The internship experience indicates an ability to work on real datasets and apply learned concepts. The project descriptions suggest an understanding of end-to-end project development, from data handling to deployment and alerting. However, without specific behavioral or teamwork assessments, a deeper evaluation of soft skills and operational fit is limited.