Spandan Tiwari
Director Of Engineering, AI Frameworks And Applications, AMD AI
Redmond, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolSpandan Tiwari is a seasoned engineering leader driving AI frameworks and product strategy, currently directing AI Frameworks and Applications at AMD to accelerate GenAI on Ryzen AI NPUs and Instinct MI300x GPUs. He has two decades of deep technical experience across LLMs, computer vision, ASR and NLP, and a proven track record building compiler, runtime and tooling integrations that connect accelerators to major ecosystems like PyTorch, ONNX/OnnxRuntime and Hugging Face. Previously at Meta he led the PyTorch compiler/runtime effort for MTIA and at Microsoft was a founding contributor to the ONNX standard and runtime, bringing cross-framework interoperability to production in Azure and edge scenarios. Known for blending research rigor with product focus, he drives advanced quantization, graph-level optimization and distributed execution features for next-generation GenAI workloads. An active open-source contributor (notably to the onnx ops and tests) who holds a PhD in electrical engineering, he pairs low-level performance optimization skills with large-scale team and roadmap leadership. Colleagues describe him as a mentor who scales talent as reliably as he scales models and runtimes.
9 years of coding experience
20 years of employment as a software developer
Bachelor of Engineering Electronics and Telecommunication, Bachelor of Engineering Electronics and Telecommunication at Maulana Azad National Institute of TechnologyPhD Electrical Engineering, PhD Electrical Engineering at Missouri University of Science and Technology
English, Hindi, Punjabi
Github Skills (9)
mle10
machine-learning10
deep-learning10
onnx10
ml10
python9
neural-network9
pytorch8
tensorflow8
Programming languages (5)
Github contributions (5)
onnx/onnx
Jan 2018 - Jan 2019
Open standard for machine learning interoperability
Role in this project:
ML Engineer
ML EngineerContributions:2 reviews, 11 commits, 23 PRs in 11 months
Contributions summary:Spandan contributed significantly to the ONNX repository by implementing and testing new operations (ops) for machine learning models. They developed tests for the Flatten, Conv, ConstantLike, EyeLike, and OneHot ops. The user also contributed to the definition of these ops and updated relevant files. Their work involved adapting the ONNX framework to support a wider range of machine learning models.
pytorchmxnetdeep-learninginteroperabilitymachine-learning
spandantiwari/pytorch
Sep 2018 - Jan 2021
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Contributions:121 pushes, 46 branches in 2 years 4 months
pythongpu-accelerationdeep-learninggpuacceleration
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