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AI Engineer with less than a year in AI/ML, LLM, and RAG systems.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
B.Tech CSE (Data Science) student with AI/ML internship experience and active LeetCode practice. Built production LLM apps, RAG pipelines, and multimodal AI systems using Python, PyTorch, LangChain, and Flask with focus on real-world deployment, performance optimization, and scalable ML architecture.
Dr. APJ Abdul Kalam Technical University
Bachelor of Technology · Computer Science Engineering (Data Science)
August 1, 2023 – June 30, 2027
HiLearn Technology
AI/ML Intern
February 1, 2026 – Present
Ahmedabad, Gujarat, India
Production Multimodal Sentiment Analysis Engine
May 1, 2026 – Present
• Fine-tuned BERT transformer model on 1,000+ samples achieving 89% accuracy in text sentiment classification across multi-class emotion categories. • Built CNN in PyTorch for audio emotion recognition using Mel-spectrogram feature extraction on RAVDESS dataset, enabling real-time audio analysis. • Deployed end-to-end multimodal web application using Streamlit for live sentiment feedback, reducing manual feedback processing time by 12+ hours/week.
Enterprise Multimodal RAG Chatbot
May 1, 2026 – Present
• Built end-to-end RAG pipeline for enterprise knowledge management, processing PDF/TXT documents using text chunking and sentence transformer embeddings. • Indexed 250+ pages of technical documentation into ChromaDB vector database achieving 94% semantic search precision and sub-3-second query latency. • Deployed containerized Streamlit application reducing documentation retrieval time by 70%.
View ProjectIntroduction to Generative AI
Google Cloud
May 1, 2026 – Present
Python Programming Certification
Infosys Springboard
May 1, 2026 – Present
Deep Learning Fundamentals (Cognitive Class)
IBM
May 1, 2026 – Present
Cultural Fit Analysis
The candidate exhibits a strong passion for applied AI/ML, evidenced by diverse projects spanning RAG, multimodal sentiment analysis, and educational AI. This indicates an innovative and proactive mindset. The emphasis on real-world deployment, performance optimization, and quantifiable impact aligns well with a product-oriented AI engineering culture. The breadth of technical skills and continuous learning initiatives suggest a growth-oriented individual who would thrive in a dynamic technical environment.
Soft Skills & Operational Fit
The candidate demonstrates a strong problem-solving orientation through complex project implementations and performance optimizations. Collaboration is evident from working in a cross-functional team environment using Git. A consistent focus on deployment and operationalizing AI models (Streamlit, Flask, Docker) indicates a practical, results-driven approach. Proactive learning is shown through multiple certifications and active LeetCode practice.