KR SHREYA
AI EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with less than a year in Machine Learning & UI/UX design.
Highly motivated and results-driven engineering student with 4 months of internship experience as a UX Intern, specializing in Machine Learning, Data Science, and UI/UX Design. Proficient in Python, Java, SQL, and various ML/DL frameworks like TensorFlow and Keras. Developed impactful projects including an LSTM-based stock prediction model, a Flask-based medicine recommendation system, and a Java-based Art Gallery Management System. Eager to apply strong analytical, technical, and problem-solving skills in a challenging AI/ML or software development role.
K S Institute of Technology
Bachelor of Engineering · Computer and Communication Engineering
August 1, 2022 – June 30, 2026
Narayana PU College
PU
June 1, 2020 – May 31, 2022
Shantiniketan High School
High School
June 1, 2010 – May 31, 2020
Continental Automotive Components (India) Pvt. Ltd., now Aumovio
UX Intern
February 1, 2026 – May 1, 2026
India
Stock Market Price Prediction using LSTM
June 1, 2026 – Present
Built an LSTM-based stock price prediction model using Python, TensorFlow, and historical market data from Yahoo Finance. Performed data cleaning, normalization, and feature engineering with technical indicators. Evaluated model performance using MAE, MAPE, and RMSE and integrated a chatbot-based Q&A feature for stock-related queries.
Medicine Recommendation Management System
June 1, 2026 – Present
Designed a Flask-based web app to recommend personalized medication, diet, and workout plans using supervised ML models (Decision Tree, Random Forest). Integrated speech recognition, BMI calculator, and period tracker to enhance user interactivity and accessibility. Utilized Python, Pandas, and classification algorithms to predict diseases based on user symptoms, with real-time recommendation generation.
Art Gallery Management System
June 1, 2026 – Present
Built a Java-based desktop application to manage art pieces, artist details, buyers, and transactions efficiently. Implemented core modules like login, inventory, and billing using Java Swing and JDBC for database connectivity. Designed a user-friendly interface for smooth navigation and ensured secure data storage using MySQL.
TechManthan – Turning Idea into Impact – Secured Second Runner-Up for presenting the business idea “Elder Ease"
Unknown
June 1, 2026 – Present
Infosys Springboard – Computational Theory: Language Principle & Finite Automata Theory
Infosys Springboard
June 1, 2026 – Present
IoT Workshop
CIIRC
June 1, 2026 – Present
Gameathon - Participated in a 24-hour game development event promoting innovation and teamwork
Unknown
June 1, 2026 – Present
Advanced Course on Green Skills and Artificial Intelligence under Skills4Future Program
Edunet Foundation & AICTE in collaboration with Shell India Markets Pvt. Ltd.
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including an LSTM-based prediction model, a Flask-based recommendation system, and a Java desktop application, shows a broad interest in different technical areas. The UX internship at Continental indicates an ability to work in a structured corporate environment and collaborate. Participation in events like TechManthan and Gameathon suggests initiative and teamwork. However, the experience is primarily academic and internship-level, which might require significant ramp-up for a senior AI Engineer role.
Soft Skills & Operational Fit
The candidate lists teamwork, communication, creativity, and willingness to learn as soft skills. Project descriptions indicate collaboration (e.g., 'collaborated with cross-functional teams' in internship) and problem-solving. The academic nature of projects suggests a structured approach to problem-solving, but real-world operational experience in AI/ML deployment is limited.