Summary
Daan Van Stigt is a senior AI research scientist with a decade of experience building multilingual LLMs and production-grade APIs for machine translation quality evaluation. At Unbabel he developed open-source, state-of-the-art quality estimation models, a multilingual LLM for translation error explanation, and an OpenKiwi PyTorch toolkit, helping the company win WMT competitions in 2022 and 2023. He combines foundational research with productization—adapting models to customer data, scaling services to millions of translations per day, and coordinating cross-functional releases. He also improved annotation pipelines by detecting and resolving annotator disagreement, making evaluation data more reliable. Based in Amsterdam with a background in logic, linguistics and liberal arts, he brings a rare mix of formal academic training and hands-on engineering. Outside of pure research he demonstrates product instincts, having built demos and public APIs that drove early LLM adoption by customers and investors.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Arts - BA, Philosophy and Linguistics, Bachelor of Arts - BA, Philosophy and Linguistics at The University of British Columbia
Bachelor of Arts - BA (cum laude), Liberal arts and sciences, Bachelor of Arts - BA (cum laude), Liberal arts and sciences at Amsterdam University College
Master of Science - MSc, Logic (ILLC), Master of Science - MSc, Logic (ILLC) at Universiteit van Amsterdam
Dutch, Spanish, portugees, English