Summary
Gjorgjina Cenikj is a machine learning engineer and recent PhD whose eight-year career bridges academic research and production ML, currently researching automated algorithm selection and representation learning at the Jozef Stefan Institute while working on time-series and satellite signal processing at Planet. She specializes in AutoML, optimization, representation learning and NLP, with practical experience deploying LLMs, recommendation engines, and cost-optimized cloud pipelines for enterprise products. Her PhD work produced methods for benchmark design, algorithm performance prediction and deep feature extraction for black-box optimization—skills she pairs with hands-on software engineering from full‑stack hospital systems to production ML services. Comfortable moving models from prototype to production, she’s adept at combining landscape analysis and meta-learning to make optimization more predictable and automated. Based in Ljubljana, she brings a researcher’s rigor and an engineer’s focus on impact, often blending deep learning architectures with practical tooling for real-world decision systems. An under-the-radar strength is her cross-domain fluency: she translates insights from satellite signals and time series into better representations for optimization and NLP tasks.
7 years of coding experience
5 years of employment as a software developer
Doctor of Science, Information and communication technologies, Doctor of Science, Information and communication technologies at Mednarodna podiplomska šola Jožefa Stefana
Bachelor of Science - BS, Computer Science and Engineering, Bachelor of Science - BS, Computer Science and Engineering at Faculty of Computer Science and Engineering - Skopje