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Kosari Ranija

Software Engineer • Hyderabad, India • k***********@gmail.com • +91*******955 • linkedin.com/••••• • drivetube.ai/•••••

Professional Summary

Software Engineer with 0 years of experience building web applications and ML prototypes using Python, Flask, and SQL. Practical experience in computer vision, NLP, and Web3 through academic projects and an AI/ML internship; strong foundation in software design, API integration, and end-to-end application deployment.

Technical Skills

Programming Languages: Python,C,JavaScript,Solidity
Web Technologies: HTML,CSS,REST APIs
Frameworks and Libraries: Flask,Streamlit,Scikit-learn,Pandas,NumPy,OpenCV
Databases: SQL
Data and Analytics: Natural Language Processing,TF-IDF,Artificial Neural Networks,Model evaluation
Tools and Methodologies: Git,GitHub,VS Code
Blockchain & Web3: Web3.py,IPFS
Core Concepts: OOP,DBMS,Data preprocessing

Work Experience

Infosys Springboard
Hyderabad, India
AI/ML Intern
Nov 2025 – Jan 2026
AI/ML internship within Infosys Springboard (Infosys training program) focused on building computer vision and ML web applications and deploying end-to-end inference pipelines.
Tech Stack: Python, OpenCV, Flask, Scikit-learn, REST APIs, Git, GitHub
  • Engineered a real-time facial emotion recognition model using Python and OpenCV trained on ~35,000 images across 6 emotion classes, achieving ~85% classification accuracy.
  • Built a data preprocessing pipeline for image normalization, labeling and augmentation to improve model generalization; used scikit-learn methods for evaluation and cross-validation.
  • Developed a Flask web application with live webcam feed and image upload endpoints for real-time inference, connecting front-end streaming to backend REST APIs for low-latency predictions.
  • Integrated third-party music recommendation APIs to create an automated recommendation pipeline triggered by detected emotions; implemented end-to-end data flow from model output to API-driven content.
  • Packaged the inference model as REST endpoints and deployed the pipeline for staging testing, validating end-to-end functionality and measuring basic runtime responsiveness during demos.
  • Managed code and collaboration using Git and GitHub; produced documentation and demo notebooks to support knowledge transfer within the Infosys Springboard cohort.
KOSARI RANIJA Software
Artificial Neural Networks
Business Analytics

Projects

Blockchain-Based Agricultural Data Security Portal | 2025 – 2026
Tools Used: Python, Flask, Web3.py, Solidity, IPFS, Streamlit, SQL
  • Architected a secure agricultural data portal using Solidity smart contracts and Web3.py to store immutable crop records and enable automated payment settlement.
  • Designed a hybrid IPFS storage model for off-chain large-file storage with on-chain references, and implemented back-end APIs in Flask and front-end screens in Streamlit.
  • Delivered 14 functional UI screens across 4 stakeholder roles and validated functionality with zero defects through iterative testing and end-to-end flows.
Fraudulent Job Posting Detection System | 2025 – 2025
Tools Used: Python, NLP, Scikit-learn, TF-IDF
  • Built a binary job scam classifier using TF-IDF feature engineering and an MLP classifier to identify fraudulent job postings versus legitimate ones.
  • Implemented data cleaning and text preprocessing pipelines and evaluated model performance against rule-based baselines, showing improved detection accuracy.
  • Packaged model inference as a script for batch scoring and documented model evaluation metrics and preprocessing steps for reproducibility.
Cyber Threat Detection System | 2024 – 2024
Tools Used: Python, Artificial Neural Networks, Scikit-learn
  • Designed an ANN-based intrusion detection prototype to classify network security events and reduce false positives in threat detection.
  • Engineered feature extraction and model training pipelines and compared ANN results with classical ML baselines using standard performance metrics.
  • Prepared evaluation reports and code notebooks demonstrating model behavior on labeled network datasets.

Education

Malla Reddy Institute of Technology (JNTU)
B.Tech in CSE • Hyderabad, India • 2022 – 2026
Alphores Junior College
Intermediate (MPC) • Hyderabad, India • 2020 – 2022
Krishnaveni High School
Secondary (SSC) • Hyderabad, India • 2019 – 2020

Certifications

Generative AI Fundamentals — GUVI, AICTE & HCLTech (SAWIT.AI Learnathon) • Oct 2024
Python Foundation Certification — Infosys • Jul 2025
Artificial Intelligence Primer — Infosys • Jul 2025
Data Visualization (Business Analytics Track) — Forage • 2024

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