Akos Mate is a data engineer with nine years of experience who blends academic rigor from a PhD track with hands-on production work in LLMs, vector databases, and cloud/noSQL pipelines. Based in Budapest, he has transitioned research-grade text mining and large-scale text classification expertise into deployable systems for institutions like the IMF and national research centres. He teaches and consults regularly, having built recommender and demand-forecasting systems for e-commerce clients while also instructing advanced methods and R courses. At IdomSoft he focuses on in-house LLM serving and observability across multiple Kubernetes clusters, demonstrating a rare mix of model-level ML competence and operational engineering. Colleagues describe him as a collaborative researcher-engineer who favors explainable, team-driven solutions and continually moves ideas from prototype to production.
9 years of coding experience
7 years of employment as a software developer
Visiting PhD Researcher, Visiting PhD Researcher at KU Leuven
Doctor of Philosophy (PhD), Doctor of Philosophy (PhD) at Central European University
International Economy and Business, MA, International Economic Analysis, International Economy and Business, MA, International Economic Analysis at Budapest Corvinus University
International Business, BA, International Business, BA at Budapesti Mûszaki és Gazdaságtudományi Egyetem / Technical University of Budapest
Contributions:30 pushes, 1 branch in 2 years 5 months
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