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AI Engineer with 2+ years in Machine Learning & NLP/Computer Vision
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Assessing your cultural and operational fit
AI-focused Machine Learning Engineer with hands-on experience building end-to-end ML and deep learning systems using Python, TensorFlow, and PyTorch. Developed NLP classification models achieving 87% accuracy and implemented YOLO-based object detection for real-world datasets. Strong foundation in model optimization, evaluation metrics, and scalable ML pipelines. Passionate about building production-ready AI systems for global remote environments.
Federal Institute of Science and Technology (FISAT)
Bachelor of Technology (B.Tech) · Electronics & Communication Engineering
August 1, 2020 – June 30, 2024
KELTRON
Intern
June 1, 2024 – September 1, 2024
India
AIASL / Cochin International Airport (CIAL)
Ground Staff - Airport Operations
March 1, 2024 – May 1, 2025
India
Sentiment Analysis System Using Machine Learning & NLP
January 1, 2025 – December 1, 2025
Designed end-to-end NLP pipeline including tokenization, lemmatization, stop-word removal, and TF-IDF feature extraction. Trained and compared Decision Tree, Random Forest, and KNN models on labelled review dataset. Improved model accuracy from 78% to 87% through hyperparameter tuning and feature optimization. Evaluated performance using Precision, Recall, and F1-score for balanced classification. Built reusable ML pipeline for scalable customer sentiment analysis.
View ProjectReal-Time Object Detection Using YOLO
January 1, 2025 – November 1, 2025
Implemented YOLO-based multi-class object detection on real-world image datasets. Applied image preprocessing, bounding box regression, and Non-Max Suppression techniques. Evaluated detection performance using Intersection over Union (IoU). Automated object recognition workflow, reducing manual inspection effort. Structured modular codebase for scalable experimentation.
View ProjectNeural Network Design & Optimization (TensorFlow & PyTorch)
January 1, 2025 – October 1, 2025
Designed and trained feedforward neural networks for classification tasks. Implemented dropout regularization and hyperparameter tuning to reduce overfitting. Improved validation accuracy from 78% to 87% via optimizer and learning rate adjustments. Evaluated models using confusion matrix and performance metrics. Developed reproducible ML experimentation workflow.
View ProjectStock Market Trend Analysis & Predictive Modeling
January 1, 2025 – September 1, 2025
Performed exploratory data analysis on historical stock datasets to analyze volatility and trend patterns. Engineered features and built regression model to predict short-term price movement. Automated data preprocessing pipeline using Pandas, reducing manual effort by 30%. Visualized insights using Matplotlib and Seaborn to support risk-aware decision-making.
Power BI /Tableau Dashboard – ICC World Cup Dataset
January 1, 2025 – August 1, 2025
Developed interactive Power BI dashboards for team and player performance analysis. Visualized KPIs to support strategic decisions and performance benchmarking.
OFF-CASE – Wireless Bluetooth Camera Gadget (Computer Vision & IoT)
January 1, 2023 – December 1, 2023
Designed a wireless Bluetooth-enabled gadget with an integrated camera to detect poisonous and non-poisonous plants. Targeted trekking and outdoor safety use cases using real-time visual identification. Applied computer vision and classification concepts for plant-type detection.
Charging Point Alerter (Embedded Systems &Automation)
September 1, 2022 – September 1, 2022
Developed an alert system that produces an audible beep when a charger is left switched ON or OFF unintentionally. Reduced energy wastage and improved electrical safety through automated alerting.
AI for Everyone
DeepLearning.AI
June 1, 2026 – Present
Machine Learning Specialization
DeepLearning.AI
June 1, 2026 – Present
Deep Learning Specialization
DeepLearning.AI
June 1, 2026 – Present
Python for Everybody
University of Michigan
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects showcase a strong interest and practical application in AI/ML, aligning well with an AI Engineer role. The diversity of projects, from sentiment analysis to object detection and embedded systems, indicates a broad curiosity and willingness to explore different domains within AI. The certifications further reinforce a proactive learning attitude. While the professional experience is not directly in AI, the transferable skills and project work suggest a good cultural fit for a role requiring problem-solving, data-driven decision-making, and continuous learning.
Soft Skills & Operational Fit
The candidate's experience as Ground Staff at an airport, while not directly technical, demonstrates transferable skills in managing high-volume data, coordinating with teams, ensuring compliance, and optimizing operational efficiency under time-sensitive conditions. These indicate strong organizational skills, attention to detail, and the ability to work in a structured environment. The internship at KELTRON provided exposure to industrial workflows and hardware debugging, suggesting adaptability and a practical mindset.