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AI Engineer with less than a year in Deep Learning & Computer Vision
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Assessing your cultural and operational fit
Fresh B.Tech graduate in CSE with specialization in AI & ML. Experienced in building intelligent systems using deep learning, computer vision, and web technologies through academic projects and a virtual internship. Eager to contribute, learn, and grow in a dynamic team environment.
Ramachandra College of Engineering
B.Tech · Computer Science Engineering (Artificial Intelligence and Machine Learning)
August 1, 2022 – June 30, 2026
Krishnaveni Junior College
Intermediate · MPC
June 1, 2020 – May 31, 2022
Vidya Vikas High School
10th Class · SSC
June 1, 2019 – May 31, 2020
AICTE- Eduskills
AI-ML Virtual Internship
July 1, 2024 – September 1, 2024
Visakhapatnam, Andhra Pradesh, India
Smart Waste Collection Management System
June 18, 2026 – Present
Developed a web-based AI-powered solution to streamline urban waste collection with features including user registration, geo-tagged pickup requests, and real-time status tracking. Integrated AI tools (ChatGPT, DeepSeek) for intelligent route optimization and scheduling of waste collection teams, improving operational efficiency. Built image upload functionality for pickup requests, enabling collection teams to assess waste volume before dispatching.
Brain Stroke Detection System Using Deep Learning
June 18, 2026 – Present
Built an AI-powered web application to classify brain MRI images into three categories: Normal, Ischemic Stroke, and Haemorrhagic Stroke using deep learning. Designed and trained two models: a custom CNN (4 convolutional blocks with Batch Normalization, MaxPooling, and Dropout) and a Hybrid Transfer Learning model using VGG16 pre-trained on ImageNet. Achieved over 95% classification accuracy with the Hybrid model using data augmentation techniques including rotation, flipping, zooming, and shearing. Developed a Flask-based web interface supporting single-model prediction, side-by-side model comparison, confidence scores, probability distributions, and training statistics visualization. Implemented privacy-by-design: uploaded MRI images are permanently deleted from the server immediately after prediction, with no patient data retention.
Cultural Fit Analysis
The candidate's academic projects showcase a diverse application of AI in healthcare (brain stroke detection) and urban management (waste collection), indicating a broad interest in solving real-world problems with AI. The specialization in AI & ML during B.Tech and the virtual internship further align with a culture focused on innovation and continuous learning in AI. The use of various AI tools and frameworks suggests adaptability and a willingness to explore different technologies.
Soft Skills & Operational Fit
The candidate demonstrates a proactive approach to learning and applying AI/ML concepts through academic projects and a virtual internship. The detailed project descriptions indicate an ability to articulate technical work clearly. The privacy-by-design implementation in the Brain Stroke Detection System suggests an awareness of ethical considerations in AI. The candidate's academic background in AI/ML aligns well with an AI Engineer role, indicating a foundational operational fit.