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AI Engineer with less than a year in Machine Learning & Data Analytics
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As an Artificial Intelligence and Machine Learning Intern with 0.7 years of experience, I specialize in developing and deploying AI-powered solutions. My expertise spans building RAG systems, creating predictive models using Random Forest, and applying comprehensive data preprocessing techniques. I am proficient in Python, JavaScript, and various AI/ML frameworks, with a strong foundation in core CS concepts and experience in developing full-stack applications.
Vignan's Institute of Information Technology
B.Tech · Computer Science Engineering (Artificial Intelligence)
August 1, 2023 – June 30, 2027
Infosys Springboard
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IBM Skills Build
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Edunet Foundation
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AI-Based Speech Analysis & Personality Insight System
June 1, 2026 – Present
Developed an AI-powered speech analysis system utilizing Whisper transcription and RAG with local LLMs. Designed a multi-agent AI architecture to provide real-time personality and communication insights. Integrated Chroma and Ollama for knowledge-backed summaries and automated reporting using Python, FastAPI, and React.
View ProjectCustomer Churn Prediction Dashboard
June 1, 2026 – Present
Developed a customer churn prediction system using Logistic Regression, Decision Tree, Random Forest, and SVM models with data preprocessing and real-time predictions. Built an interactive dashboard with risk scoring, model comparison, and customer retention recommendations.
View ProjectNeural Networks, Deep Learning
Infosys Springboard
June 1, 2026 – Present
HTML, CSS, JavaScript Essentials(1&2), Python Essentials(1&2)
Cisco Networking Academy
June 1, 2026 – Present
Google AI-ML Virtual Internship
EduSkills
June 1, 2026 – Present
GenAI Virtual Internship
EduSkills
June 1, 2026 – Present
Android Development Virtual Internship
EduSkills
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse engagement in academic projects, multiple internships, competitive programming, and open-source contributions suggests a strong drive for learning and contribution. Their involvement in hackathons and open-source projects indicates a collaborative spirit and a willingness to engage with the broader tech community. The breadth of skills, from core programming to AI/ML and full-stack development, shows adaptability and a holistic approach to problem-solving, which are positive indicators for cultural fit in a dynamic engineering environment.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and a proactive learning attitude through multiple internships, certifications, and competitive programming achievements. Their project descriptions indicate an ability to work on end-to-end solutions, from model development to UI/backend integration. The focus on AI/ML aligns well with an AI Engineer role, suggesting a good operational fit for a team working on similar technologies. However, the experience level is entry-level, which might require more guidance in a senior role.