Summary
Bence Tilk is a software engineer specializing in machine learning with 11 years of experience solving hard ML problems across image, audio, NLP and signal domains. Currently at Meta, he focuses on enabling and optimizing models for a custom AI accelerator and improving kernels and ML compilers, building on prior work at Graphcore integrating IPUs with PyTorch and cloud environments. He has a strong applied-research background—developing domain adaptation tools that placed in ICCV challenges and prototyping document-structure and chat-understanding systems—while retaining a taste for principled approaches like Bayesian methods and RL. Comfortable across the stack from low-level kernel optimization to distributed ML frameworks like Ray, he blends theory-minded curiosity with production-grade delivery. Based in Oslo, he holds an MSc in Computer Engineering and often seeks projects that push both theoretical understanding and real-world performance.
11 years of coding experience
7 years of employment as a software developer
Master of Science - MS, Computer Engineering, Master of Science - MS, Computer Engineering at Budapest University of Technology and Economics
Exchange student, Computer Science, Exchange student, Computer Science at Technical University of Munich
English, German, Hungarian