I've built and evaluated agent workflows for Google Gemini-related systems at Turing, using MCP, RLHF, transformer fine-tuning, prompt optimization, LangChain, and HuggingFace Transformers to improve inference quality and reliability.
At VR Superstore, I delivered machine learning solutions for search, recommendation, content generation, demand forecasting, and product affinity. I built production pipelines with Python, PySpark, Databricks, Delta Lake, and MLflow, including RAG workflows and multimodal recommendation models.
I'm completing an MSc in Robotics and Automation while researching Powder Bed Fusion Electron Beam defect detection at Freemelt. My work spans reproducible data workflows, computer vision, model evaluation, analytics, and production ML delivery.

