Summary
Daniel Korzekwa is a Deep Learning Manager with 15 years of experience building production-grade ML systems and teams across speech, NLP, and high-performance computing. He has led research-to-product efforts at Amazon—delivering speech synthesis and conversion technologies used by millions—and now focuses on AutoML and ML efficiency for TTS/ASR/NLP at NVIDIA. His background spans Bayesian and Gaussian-process modeling, real-time risk systems for betting, and large-scale distributed monitoring platforms, reflecting both strong research credentials (PhD in Machine Learning for Speech) and hands-on engineering in Scala, Java, and HPC environments. Known for growing research teams from scratch and publishing at major conferences, he combines academic rigor with pragmatic delivery at cloud and hardware scale. Based in Gdańsk, Poland, he brings a rare blend of deep speech expertise and systems-level engineering that accelerates ML models from prototype to high-throughput production.
15 years of coding experience
Doctor of Philosophy - PhD, Machine Learning in Speech Processing, Doctor of Philosophy - PhD, Machine Learning in Speech Processing at Gdańsk University of Technology
MSc, Computer Science, MSc, Computer Science at Politechnika Śląska w Gliwicach
Polish, English