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AI Engineer with less than a year in Python & Data Science
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Assessing your cultural and operational fit
Final Year Student B-TECH CS with Specialization in Artificial Intelligence and Machine Learning with good hands practice on Python and ML libraries including Pandas, NumPy and Matplotlib. Seeking for an entry level role.
gla university
Bachelor of Technology · Computer Science
August 1, 2022 – June 30, 2026
Oil Spill Detection System
June 20, 2026 – Present
Developed an end-to-end object detection pipeline using YOLOv5 to identify oil spill from satellite images. Automated data preprocessing by monitoring Google Drive and programmatically generating YAWL configuration files for seamless model training. Implemented experiment tracking and model logging using Weights and Biases to monitor loss metrices and mean average position. Optimized detection performance by fine-tuning hyperparameters over 50 epochs, achieving a high-confidence threshold for environment monitoring.
Vehicle Price Prediction
June 20, 2026 – Present
Utilized Random Forest Regression to solve a complex pricing estimation problem, handling both numerical and categorical data. Executed exploratory data analysis to identify correlations between vehicle features and market price. Built an end-to-end pipeline from data cleaning in pandas to model deployment via Flask.
Software Engineer Simulation
JP- Morgan
June 1, 2026 – Present
Data Visualization
Tata
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate an interest in applying AI/ML to real-world problems (oil spill detection, vehicle price prediction, cow health classification). The certifications from JP-Morgan and Tata indicate an initiative to gain industry exposure. While the projects are diverse in application, they are all academic. The candidate is a final-year student seeking an entry-level role, which aligns with a learning and growth-oriented culture. However, the breadth of experience is limited to academic settings.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems and a structured approach to development (e.g., end-to-end pipelines, experiment tracking). However, without direct assessment data, specific soft skills like teamwork, problem-solving under pressure, or communication style cannot be definitively evaluated. The academic nature of projects suggests a learning-oriented individual.