David Mosallanezhad
Senior Deep Learning Applied Scientist, AI at NVIDIA
Tempe, Arizona, United States
Summary
🤩
Rockstar🎓
Top SchoolDavid Mosallanezhad is a Senior Deep Learning Applied Scientist at NVIDIA and a PhD candidate in Computer Science at Arizona State University with seven years of experience building and deploying ML systems. He specializes in NLP and reinforcement learning research, bridging academic rigor (MSc in AI, 4.0) with production-focused MLOps work. At NVIDIA he has driven CI/CD and testing infrastructure for high-profile projects like the NeMo Framework Launcher, streamlining model performance measurement and release pipelines. David combines hands-on model development and systems engineering, making him equally comfortable with research experiments and scalable deployment. Based in Tempe, he brings a track record of accelerating model delivery from lab to production while maintaining a strong publication-oriented research program.
7 years of coding experience
3 years of employment as a software developer
Master of Science - MS, Artificial Intelligence, 4.0, Master of Science - MS, Artificial Intelligence, 4.0 at Shiraz UniversityDoctor of Philosophy - PhD, Computer Science, 4.0, Doctor of Philosophy - PhD, Computer Science, 4.0 at Arizona State University
Github Skills (16)
docker10
dockers10
cicd10
testing10
performance-monitoring9
performance-measurement9
python9
performance-analytics9
performance-monitor9
performance-analysis9
performance-tuning9
bash8
machine-learning8
yaml7
kubernetes6
Programming languages (3)
Github contributions (5)
NVIDIA/NeMo-Framework-Launcher
Oct 2022 - Dec 2022
Provides end-to-end model development pipelines for LLMs and Multimodal models that can be launched on-prem or cloud-native.
Role in this project:
MLOps Engineer
MLOps EngineerContributions:5 releases, 7 reviews, 32 commits in 2 months
Contributions summary:David primarily contributed to the continuous integration and continuous deployment (CI/CD) pipelines and testing infrastructure within the repository. This included updating container versions, modifying test configurations, and integrating performance measurement tools for models. The contributions focused on streamlining the testing and release processes for various machine learning models. The user's changes also touch on integrating and configuring the system for measuring performance.
Davood-M/davood-m.github.io
Oct 2019 - Jun 2022
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Contributions:65 pushes, 2 branches in 2 years 8 months
templategithub-pages-templatemmistakesmistakesjekyll
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