I'm a software engineer experienced in building enterprise-grade applications, with proven experience delivering real-time ML systems, recommendation engines and RAG-based pipelines. I'm adept in cloud-native development, LLM integration and data-centric problem solving, and passionate about building scalable AI systems that solve real-world challenges.
I'm currently at Avirso, building AI and backend systems for fintech and enterprise finance. Before that I was a machine learning engineer at Brain Box Automations. My journey in technology began with cybersecurity at FAST University, but I found my true calling at the intersection of artificial intelligence and real-world problem solving.
My work spans recommendation systems, natural language processing, computer vision and cloud infrastructure. I've contributed to open source through Google Summer of Code and been recognized for enhancing security in educational platforms.
When I'm not coding, I explore the latest developments in AI research, contribute to the tech community and experiment with new AI tools. I believe in the power of technology to create positive change, and I'm always excited to work on projects with meaningful impact.
Where I've worked and what I shipped.
Selected systems, from model to production.
Comprehensive recommendation system supporting multiple recommendation types: Top Picks, Because You Watched, More Like X, Trending Now and Most Popular. Implemented real-time user interaction tracking and automated model retraining workflows, with cold-start resolved through discovery strategies.
Intelligent voice chatbot that automates appointment scheduling with natural language processing, real-time calendar integration and multi-platform support.
AI system that automatically identifies high-severity issues from support transcripts using fine-tuned transformer models, enabling prioritization of safety-critical cases.
Interactive dashboard for inventory demand forecasting integrating multiple time-series models (ARIMA, Prophet, TimeGPT, TimesFM). Advanced smoothing and seasonal decomposition (STL), with dynamic visualizations and evaluation metrics (MAE, RMSE, MAPE) to enhance forecast accuracy.
Customized chatbot using Streamlit, Chroma and FastEmbedEmbeddings for interactive querying of ISO 27001, NIST SP 800-53, GDPR, HIPAA, PCI DSS and other security policy documents — enabling real-time answers that enhance compliance checks and policy understanding.
Automated hierarchical product taxonomy classification using a Retrieval-Augmented Generation architecture with embedding-based semantic search over vector databases, slashing manual catalog mapping time.
Graduated with comprehensive knowledge in cybersecurity, artificial intelligence and software development. Completed 130 credit hours covering advanced topics in network security, cryptography, machine learning and software engineering practices.
Got an idea, a question, or just want to talk AI and backend systems? My inbox is open.