Andrei-cristian Rad
Lead Machine Learning Engineer at JWX
Cluj-Napoca, Cluj, Romania
Summary
👤
Senior🎓
Top SchoolAndrei-cristian Rad is a technical leader with 8 years of experience building production ML and data science systems, currently managing Machine Learning & Data Science at JWX in Cluj-Napoca. He combines hands-on engineering—authoring model training platforms on SageMaker, Airflow orchestration, and MLflow experiment tracking—with strategic product work that lifted publisher revenue and cut cloud spend. His work in programmatic advertising spans real-time bidding optimizations (including a QPS-reducing filter with no revenue loss) and predictive audience engines that improved CTR by up to 15%. He has applied similar MLOps rigor in healthcare and competitive intelligence, shipping semantic segmentation tools and entity-relation extraction systems. Pursuing a PhD in AI, he also researches robustness, fairness, and explainability for LLMs and VLMs, bringing a research-informed perspective to production constraints. Colleagues know him as a pragmatist who “eats text data for breakfast,” blending deep NLP instincts with measurable business impact.
9 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Artificial Intelligence, Doctor of Philosophy - PhD, Artificial Intelligence at Technical University of Cluj NapocaMaster of Applied Sciences, Applied Computer Science, Thesis - 19/20, Master of Applied Sciences, Applied Computer Science, Thesis - 19/20 at Vrije Universiteit Brussel"Emil Racoviță" National College
French, English
Stackoverflow
133reputation
53kreached
8answers
1question
Github Skills (59)
geometric-deep-learning10
pytorch10
deep-learning10
cython10
graph-neural-network10
graph-convolutional-networks10
data-science9
artificial-intelligence9
named-entity-recognition9
entity-linking9
python9
text-classification9
machine-learning9
natural-language-processing9
ai9
Programming languages (6)
Github contributions (5)
radandreicristian/traffic
Nov 2021 - May 2022
An end-to-end traffic forecasting training pipeline and a collection of PyTorch traffic forecasting models that use graph neural PDEs and sub-quadratic attention.
Contributions:5 commits, 2 PRs, 79 pushes in 6 months
forecasting-modelsgraphpytorch
radandreicristian/nlu
Apr 2020 - Jun 2021
Contributions:2 PRs, 25 pushes, 5 branches in 1 year 2 months
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