Daniel Noronha
Machine Learning Engineer at AMD
Vancouver, British Columbia, Canada
Summary
👤
Senior🎓
Top SchoolDaniel Noronha is a machine learning engineer with 11 years of experience specializing in accelerating ML workloads from research to product. He has driven productization of model-to-hardware toolchains—co-leading GroqFlow at Groq and now contributing ML systems at AMD—while shipping performance wins for vision and NLP models like BERT, RoBERTa, ViT, and DETR. His PhD from UBC focused on debugging and understanding AI training on advanced architectures, and he published a popular open-source toolchain (500+ stars) that maps TensorFlow computations to hardware. Past roles at Microsoft Project Brainwave and in HPC broadened his expertise in emulation, FPGA/accelerator tooling, and parallel performance tuning. Based in Vancouver, he blends deep hardware-aware ML knowledge (BFP quantization, distillation, sparsity exploitation) with a product-minded approach to developer velocity. Colleagues rely on him to turn complex compiler and systems research into shipping, maintainable software.
11 years of coding experience
7 years of employment as a software developer
Federal University of Rio Grande do NorteExchange, Computer Engineering, Exchange, Computer Engineering at Rensselaer Polytechnic InstituteExchange, Computer Engineering, Exchange, Computer Engineering at Technische Universität BerlinDoctor of Philosophy - PhD, Computer Engineering, Doctor of Philosophy - PhD, Computer Engineering at The University of British Columbia
English, German, Portuguese
Github Skills (44)
benchmark10
x8610
nvidia10
smith-waterman10
evaluation9
pytorch9
llm9
onnx9
synthesis9
toolchain9
gpu9
ai9
fpga9
cuda9
nlp8
Programming languages (6)
Github contributions (5)
danielholanda/LeBug
Apr 2020 - Mar 2021
Contributions:260 commits in 11 months
groq/mlagility
Jan 2023 - Jul 2023
Machine Learning Agility (MLAgility) benchmark and benchmarking tools
Contributions:286 reviews, 100 PRs, 401 pushes in 5 months
managed-by-terraform
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