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AI Engineer with less than a year in Python & Generative AI
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Graduated B.Tech (Artificial Intelligence) with hands-on experience designing, developing the software applications in Python. Skilled in working with databases, ML Models, AI tools that follow defined design specifications, and applying GenAI and computer networking concepts to deliver functional, well-tested software.
Madanapalle Institute of Technology & Science
B.Tech · Artificial Intelligence
August 1, 2021 – June 30, 2025
Sri Chaitanya Junior College
Higher Secondary Education
June 1, 2018 – May 31, 2020
DAV Public High School
SSC
June 1, 2015 – May 31, 2018
Upskill
Python Intern
June 1, 2023 – July 1, 2023
India
RAG-Based Intelligent Document Assistant
June 1, 2026 – Present
Designed and developed a Retrieval-Augmented Generation (RAG) application in Python to debug and resolve context-retrieval gaps in document-based question answering. Built and tested core software modules for document loading, text chunking, and vector embedding generation, troubleshooting accuracy issues to improve relevance of retrieved results. Integrated Google Generative AI embeddings with a conversational LLM pipeline, debugging API and data-flow issues to deliver a stable knowledge-retrieval tool.
Student Performance Prediction
June 1, 2026 – Present
Developed a machine learning model to predict student academic performance using Linear Regression. Performed data preprocessing, feature engineering, and exploratory data analysis using Pandas and NumPy. Evaluated model performance using MAE, MSE, and R2 metrics, achieving over 90% prediction accuracy. Visualized student performance trends using Matplotlib and Seaborn to identify key factors affecting exam scores.
Introduction to Technology Apprenticeship Job Simulation
Accenture UK
June 1, 2026 – Present
Acquiring Data
Nasscom
June 1, 2026 – Present
Google Data Analytics
Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects show an interest in both traditional machine learning and generative AI, indicating adaptability and a willingness to explore different areas within AI. The personal projects suggest initiative and self-driven learning. The internship, while brief, shows an early exposure to professional coding. The academic achievements and extracurriculars suggest a well-rounded individual. However, the overall breadth of experience is limited due to the candidate's early career stage.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to debug and troubleshoot, suggesting problem-solving skills. Participation in NSS and district-level sports implies teamwork and discipline, which are positive indicators for operational fit. However, the limited professional experience makes it difficult to fully assess operational fit in a corporate environment.