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AI Engineer with less than a year in Machine Learning, NLP, and Full-stack Development
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated Computer Science and Engineering student with a solid foundation in AI, Machine Learning, and full-stack development. Experienced in building conversational AI chatbots, personality evaluation systems, and spam classifiers. Proficient in Python, Java, and C, with a strong understanding of various technical tools and frameworks. Seeking to apply analytical and problem-solving skills in an innovative tech environment.
JNTUH College Of Engineering Manthani
Bachelor of Technology · Computer Science and Engineering (AI&ML)
August 1, 2021 – June 30, 2025
Kakatiya Junior College
Intermediate · MPC
June 1, 2019 – May 31, 2021
Chaitanya High School
Secondary School Certificate · SSC
June 1, 2018 – May 31, 2019
Personality Evaluation System
January 1, 2024 – May 31, 2025
Developed an ML-powered intelligent system to evaluate personality traits from resume data and textual inputs. Extracted linguistic and behavioral features using NLP to classify candidates into Big Five personality dimensions. Applied Logistic Regression and Decision Tree classifiers for predicting core personality traits. Built an intuitive web interface for uploading CVs and clearly displaying trait-based profiling results.
SQL Chatbot using LLM
January 1, 2024 – May 31, 2025
Built a conversational AI chatbot that translates natural language questions into accurate SQL queries using LLMs. Integrated LangChain and Gemini API to dynamically construct and safely execute SQL queries. Used Streamlit dashboard for front-end interaction and Pandas for dynamic database table querying and display results. Handled query validation and error messages to enhance chatbot reliability and user experience robustness.
Spam Email Classifier
January 1, 2024 – May 31, 2025
Built a robust spam detection system using machine learning models and natural language preprocessing. Cleaned email data, removed noise (stopwords, punctuation), and applied TF-IDF for feature extraction. Trained Naïve Bayes and SVM classifiers, achieving up to 98.94% accuracy in detecting spam emails. Serialized model and vectorizer with pickle for deployment-ready use. Visualized results using Matplotlib and Seaborn.
AI Upskilling Certificate: Technical Foundation
Qualcomm Academy
June 1, 2026 – Present
The Complete Python Pro BootCamp
Udemy
June 1, 2026 – Present
Responsive Web Development
Topcoder Academy
June 1, 2026 – Present
Data Structures and Algorithms using Java
FreeCodeCamp
June 1, 2026 – Present
Machine Learning
Simplilearn
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and foundational skill set in AI and Machine Learning, aligning well with a Data Science Engineer role. The diversity of projects (LLM chatbot, personality evaluation, spam classification) indicates a broad curiosity and willingness to tackle different problem domains within data science. The listed certifications further support a proactive learning attitude. However, all projects are academic, and there is no professional experience, which limits the assessment of cultural fit in a corporate environment.
Soft Skills & Operational Fit
The candidate lists soft skills such as Time Management, Team Collaboration, Problem Solving, Detail-Oriented, and Adaptable. These are valuable for operational fit in a data science engineering role, which often involves complex problem-solving, collaborative development, and iterative project management. However, these are self-reported and not validated by assessment data.