Zenodia Charpy
EMEA NVIDIA AI Technology Center Industry Lead
Greater Gothenburg Metropolitan Area Sweden
Summary
👤
Senior🎓
Top SchoolZenodia Charpy is an EMEA AI industry lead at NVIDIA with a decade of hands-on experience turning generative AI research into production-grade systems, from multi-agent architectures and multimodal RAG to scalable deployments serving 10x concurrent users. She designs agentic systems with memory, observability and safety guardrails, and has practical experience fine-tuning and training LLMs across distributed NVIDIA superPODs. A prolific open-source contributor, she has supported developer communities through NVIDIA repos and helped develop GPU bootcamp materials focused on Megatron-LM model-parallel training. Comfortable bridging research and engineering, she partners with consortia to architect test-driven, sovereign AI solutions across finance, gaming and research domains. Based in Gothenburg, she combines deep statistical training with hands-on ML engineering to rapidly prototype and scale innovative AI products.
10 years of coding experience
12 years of employment as a software developer
R for data scientist specialisation R programming, R for data scientist specialisation R programming at DataCamp -data science school specialized in R courses(via edx.org)Math including applied statistic and statistic modelling, Math including applied statistic and statistic modelling at Soochow UniversityScalable Machine Learning, Scalable Machine Learning at BerkeleyX-CS190.1x Scalable Machine LearningData Scientist's Toolbox Data science, Data Scientist's Toolbox Data science at Johns Hopkins Bloomberg School of Public HealthUniversity of California Santa CruzPython, Python at Code Academy - Python 100% completionMaster Information Technology(Computer Science), Master Information Technology(Computer Science) at Bond Universitysingle course (online course from coursera) duration 8 weeks Applied Logistic Regression, single course (online course from coursera) duration 8 weeks Applied Logistic Regression at The Ohio State UniversityMining of Massive Dataset Data Science Machine Learning Big Data, Mining of Massive Dataset Data Science Machine Learning Big Data at Stanford University
English, Swedish, Chinese
Github Skills (10)
cuda10
pytorch10
machine-learning10
gpu10
parallelization10
pipelining10
pipe10
pipeline10
deep-learning9
data-science8
Programming languages (5)
Github contributions (5)
openhackathons-org/gpubootcamp
Aug 2021 - Oct 2021
This repository consists for gpu bootcamp material for HPC and AI
Role in this project:
ML Engineer
ML EngineerContributions:36 commits, 1 PR, 1 comment in 1 month
Contributions summary:Zenodia contributed to the development of the Swedish GPTBootcamp tutorials, specifically focusing on the fundamentals of the Megatron-LM model and model parallelism. They modified and added Jupyter Notebooks, including code examples related to tensor and pipeline model parallelism, with a strong emphasis on the configuration of GPU affinity and practical hands-on examples. The contributions are heavily centered around the Megatron-LM framework, focusing on model-parallel training of large language models.
cudampiopenaccdata-sciencedeep-learning
Zenodia/PyTorch_DeepLearning
Oct 2017 - Jun 2020
Contributions:13 commits, 11 pushes, 1 branch in 2 years 8 months
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