Nicolas Modrzyk is a seasoned technology executive and consultant with 17 years of experience designing cloud-native architectures, scaling engineering organizations, and delivering mission-critical systems across Asia, Europe, and the US. He has led global teams of up to 300 engineers, driven multi-million-dollar AWS migrations supporting high-throughput financial platforms, and introduced AI/ML and blockchain solutions into production. As CTO and founder-level operator, he blends hands-on engineering (Go, Java, Python, Clojure) with strategic C-suite engagement and pre-sales for complex FinTech and big-data programs. An active open-source contributor, he improved robustness in Apache MXNet’s Clojure bindings by adding specs, tests, and integration checks—evidence of his attention to correctness in ML tooling. Multilingual and Japan-based, he uniquely combines cross-cultural leadership with deep expertise in LLM fine-tuning, Kubernetes/Terraform infrastructure, and enterprise-grade smart contract work.
17 years of coding experience
9 years of employment as a software developer
Master, Master at ESIAL
Gabriel Faure High School
Master, Master at Dublin City University
english (master's degree level), french (mother tongue), japanese (jplt1), Chinese
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Role in this project:
Back-end Developer & QA Engineer
Contributions:5 commits, 3 PRs, 17 comments in 1 month
Contributions summary:Nicolas contributed to the Apache MXNet Clojure package by adding specification validations to optimizer and random namespaces, and also implemented validations in test files. The user's work focused on ensuring the correctness and robustness of the library's Clojure interface, specifically related to optimizers and random number generation. Their contributions included adding specs and unit tests, ensuring that the project is well tested. Furthermore, they focused on turning examples into integration tests, improving the testing coverage.
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