Computer Science Graduate from MIT Academy of Engineering, Pune & AI/ML Intern at Expleo Group. I build intelligent systems — from LLM pipelines and RAG architectures to deep learning models — transforming complex data into practical, real-world solutions. IEEE Published Author.
I'm Om Bhutkar, an AI/ML Engineer and Computer Engineering graduate from MIT Academy of Engineering, Alandi, Pune. My work sits at the intersection of research and engineering — turning advanced AI concepts into practical, scalable, and production-ready systems.
I have experience building intelligent AI solutions across LLMs, RAG architectures, deep learning, and AI-powered automation. During my internship at Expleo Group, I worked on intelligent automation for automotive manufacturing, including PFMEA risk prediction, root cause analysis systems, and AI-powered documentation platforms using LangChain, RAG, and LLMs.
My research on AI-powered resume analysis has also been published in IEEE Xplore, reflecting my interest in combining academic research with real-world AI engineering. I'm passionate about building intelligent systems that solve meaningful problems and continuously exploring the evolving landscape of AI and machine learning.
Automated analysis of Indian classical music using a CNN + LSTM pipeline. Real-time raga classification via spectrogram analysis, confidence-weighted predictions, and automated PDF report generation with pitch contour visualisation.
AI-powered resume analyser that scores 10+ resume sections using TF-IDF and Naive Bayes, predicts career paths, matches jobs via API, runs an AI interview module, and provides an admin analytics dashboard with K-Means clustering. IEEE Published.
Pulls real-time financial news via News API, runs sentiment scoring, and overlays scores against asset price movements on an interactive dashboard with date-range and asset filters.
• Developed an AI Chatbot for IPC Section Assistance.
• Used NLP and keyword extraction to interpret user queries.
• Retrieved relevant IPC sections based on query context.
• Integrated dictionary APIs for accurate legal terminology.
• Ensured quick and reliable legal guidance for users.
Published research on an AI-based resume analysis system leveraging NLP for automated parsing, scoring, and recommendation. The system enhances recruitment efficiency by providing data-driven insights for recruiters and actionable feedback for job applicants.
ResuMate AI presents a multi-layered intelligent framework combining TF-IDF vectorisation, Naive Bayes classification, and K-Means clustering to deliver ATS-optimised scoring, personalised recommendations, and interview simulation — bridging the gap between candidates and recruiters.
Innovative multi-model generative AI framework designed for dynamic synthesis of educational resources. Leverages Transformers, GANs, VAEs, and Diffusion Models to automatically generate personalized learning materials including summaries, notes, MCQs, and STEM visuals—enabling adaptive and accessible learning systems.
EduGen demonstrates a comprehensive multi-model architecture integrating state-of-the-art generative models to synthesize dynamic, personalized educational content. The framework generates AI-powered summaries, study notes, assessment questions, and STEM visualizations—advancing intelligent, scalable, and accessible learning ecosystems.
I'm actively looking for full-time roles and internships in AI/ML and software engineering. If you have an interesting problem, I'd love to hear about it.