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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
Developer with strong adaptability and a quick learning ability for new technologies. Skilled in Python, Machine Learning, Deep Learning, and Computer Vision, with hands-on experience through an AICTE internship and real-time projects such as driver drowsiness detection, fake profile detection, and speech processing. Passionate about solving real-world problems, writing clean code, and contributing effectively in collaborative team environments.
Malla Reddy University
B.Tech · Artificial Intelligence & Machine Learning
August 1, 2021 – June 30, 2025
Sri Chaitanya Junior College
Intermediate · MPC
N/A – May 31, 2021
Spr School Of Excellence
SSC
N/A – May 31, 2019
AICTE & EduSkills
AI-ML Virtual Internship
May 1, 2023 – July 31, 2023
India
Fake Profile Detection using Machine Learning
June 1, 2026 – Present
Developed a machine learning system using Random Forest and SVM to detect fake social media profiles, achieving 90% accuracy. Designed a visualization interface that improved manual review efficiency by 30% and enhanced clarity of detection results. Tools: Python, Scikit-learn, NLP Libraries, Seaborn.
Online Stock and Inventory Management System
June 1, 2026 – Present
Developed a complete inventory management application supporting real-time stock updates, automated reordering, and sales tracking. Achieved 98.45% accuracy in monitoring inventory levels and implemented systematic categorization for 100+ product types. Tools: Python, SQL, HTML, CSS, JavaScript.
Sales Analysis Dashboard using Power BI
June 1, 2026 – Present
Developed an interactive dashboard analyzing 2.3M+ sales data, visualizing regional performance, product categories, and sales trend. Performed data transformation using Power Query and created DAX measures for KPIs like total sales, profit, and discount analysis. Tools: Power BI, DAX, Power Query.
Safe Drive Vision – Driver Drowsiness Detection System
June 1, 2026 – Present
Developed a real-time driver drowsiness detection system using webcam feed. Utilized facial landmarks to monitor blinking and yawning, applied deep learning for fatigue detection, and built a GUI interface with live video and alert notifications. Tools: Python, OpenCV, dlib, DeepFace, Tkinter, Deep Learning.
Introduction to Cloud Computing
Unknown
June 1, 2026 – Present
Exploratory Data Analysis for Machine Learning
Coursera
June 1, 2026 – Present
Computer Networking
Illinois Tech
October 1, 2023 – Present
AWS Academy Cloud Foundations
AWS
August 1, 2023 – Present
AI-ML Virtual Internship
AICTE & EduSkills
May 1, 2023 – Present
Cultural Fit Analysis
The candidate demonstrates a strong interest in AI and NLP-based innovation, problem-solving, and competitive programming, which aligns well with a dynamic, tech-driven culture. Their involvement in community mentoring and leadership roles suggests a collaborative and supportive mindset. The diversity of personal projects, from data analysis to real-time detection systems, indicates adaptability and a broad interest in applying AI/ML across different domains.
Soft Skills & Operational Fit
The candidate's profile highlights problem-solving, communication, and teamwork as soft skills. Project descriptions suggest an ability to work on real-world problems and contribute to collaborative environments. Participation in hackathons and leadership roles further supports operational fit, indicating initiative and organizational skills.