Levin Dabhi
Machine Learning Compiler Engineer at Qualcomm
Cork, Ireland
Summary
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Senior🎓
Top SchoolLevin Dabhi is a Machine Learning Compiler Engineer with eight years of experience optimizing AI workloads for GPUs and specialized accelerators, currently driving compiler and kernel performance at Qualcomm. He has a proven track record building high-performance deep learning kernels and compiler passes (operator splitting, graph partitioning) at Intel and startups, focused on squeezing maximum throughput and efficiency from hardware. Comfortable with C++, Python, and MLIR-based compiler infrastructure, Levin bridges low-level performance engineering with practical model deployment needs for both training and inference. His background spans R&D for low-power accelerators, computer vision projects (high-res virtual try-on and background removal), and robotics reinforcement learning, giving him a broad systems-and-ML perspective. Based in Cork, Ireland, he publishes work and code on GitHub and maintains a personal site showcasing his applied research and tools for AI hardware acceleration.
8 years of coding experience
6 years of employment as a software developer
Bachelor of Technology - BTech Computer Science, Bachelor of Technology - BTech Computer Science at Nirma University
Stackoverflow
1reputation
0reached
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Github Skills (68)
image-matching10
try-on10
re-identification10
siggraph9
openai-gym9
audio9
style-transfer9
python9
stylegan9
generative-adversarial-network9
pytorch9
algorithms9
image-segmentation9
nlp8
pre-trained-model8
Programming languages (6)
Github contributions (5)
levindabhi/SieveNet
Sep 2020 - Jun 2021
This is the unofficial implementation of SieveNet: A Unified Framework for Robust Image-Based Virtual Try-On
Contributions:29 commits, 3 PRs, 7 pushes in 8 months
virtual-try-onobject-detectioncomputer-visionre-identificationimage-matching
levindabhi/Self-Correction-Human-Parsing-for-ACGPN
Oct 2020 - Jun 2021
An out-of-box human parsing representation extractor.
Contributions:15 commits, 2 PRs, 15 pushes in 8 months
parsing
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