About me
Solving problems that felt out of reach, that's what pulled me into AI and it still does. Every project is the same question: can this actually work, at scale, in the real world? Answering it is the work I care about most. Lately that's meant building agentic systems that can reason, act, and be held accountable, alongside deep work in NLP, computer vision and MLOps.
My path into AI started with a simple question: how do you turn raw data into something worth knowing? While running an online shop, I got hooked on making sense of customer feedback through sentiment analysis and that small spark of curiosity became a career. It led me to a master’s degree in AI, where I found my calling as a programmer and machine learning engineer.
Since then, I’ve poured myself into the work, sharpening my craft and shipping AI that earns its place in the real world. I specialise in 𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 that reason and act, 𝗳𝗶𝗻𝗲-𝘁𝘂𝗻𝗶𝗻𝗴 𝗹𝗮𝗿𝗴𝗲 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗺𝗼𝗱𝗲𝗹𝘀 and designing 𝗡𝗟𝗣 and 𝗰𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝘃𝗶𝘀𝗶𝗼𝗻 solutions, all built to run at scale with 𝗗𝗼𝗰𝗸𝗲𝗿, 𝗠𝗟𝗳𝗹𝗼𝘄 𝗮𝗻𝗱 𝗖𝗜/𝗖𝗗 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 behind them.