Toni Kukurin is a Deep Learning Engineer with a decade of experience applying NLP and ML research to production systems, currently building DL models and infrastructure at QuantCo. He combines academic rigor (MS in Computer Science focused on NLP) with hands-on engineering across companies including Bloomberg, Google and Microsoft, where he shipped distributed training pipelines, KubeFlow model serving, and data-efficient domain adaptation solutions. Toni has a track record of turning research ideas into robust production features—examples include confidence scoring for open-domain QA, synthetic data generation and accessibility algorithms at Google, and weak-labeling approaches that outperformed production models. He regularly bridges applied research and MLOps, automating data versioning, refactoring legacy code, and improving serving latency through algorithmic and heuristic optimizations. Based in Croatia, he also has broad backend experience from internships and freelance work, and an appetite for practical, cost-saving data strategies demonstrated to reduce labeling needs by up to 80%.
10 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Faculty of electrical engineering and computing, University of Zagreb
Certificate, iOS programming, Certificate, iOS programming at Infinum Academy
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