Presentation
With 4 years of experience as a Research Data Scientist II, I bridge the gap between cutting-edge research and scalable production systems. I specialize in moving businesses beyond basic automation into the realm of Autonomous Agentic Systems and Custom-tuned Deep Learning models.
What I Offer:
1. Agentic AI & Orchestration: Designing sophisticated multi-agent workflows using LangGraph and Pydantic. I specialize in converting complex logic into executable structures, such as my proprietary Code-to-BPMN automation engine built on call-graph architectures.
2. Deep Learning & LLM Fine-tuning: Expert in the full lifecycle of neural networks—from pre-training specialized architectures to fine-tuning LLMs (PEFT/LoRA) for niche domain tasks. I ensure models are optimized for both performance and inference efficiency.
3. Classical Machine Learning: Strong foundation in statistical modeling and classical ML (Regression, Tree-based models, Clustering). I select the right tool for the job, whether it’s a lightweight XGBoost model or a massive Transformer.
4. LLM Reliability & RAG: Industry-leading expertise in hallucination detection and RAG optimization. I build "fail-safe" AI systems that meet enterprise-grade security and accuracy standards.
5. End-to-End MLOps: Full-stack deployment on GCP and AWS, ensuring your models are monitored, versioned, and scalable.
The Technical Edge:
I don't just build chatbots; I build intelligent infrastructure. My background in hallucination research means your AI will be reliable, and my experience in deep learning ensures your models are uniquely tailored to your data.
Tech Stack: Python, PyTorch, TensorFlow, LangChain/LangGraph, HuggingFace, SQL, GCP, Scikit-Learn.

