Sumit Agarwal
Software Engineer II at Microsoft
Bellevue, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolSumit Agarwal is a Software Engineer II specializing in GPU-accelerated ML infrastructure and runtime performance, currently working at Microsoft to speed up AI inference through DirectML and ONNX Runtime. With six years of industry experience and an MS in Computer Science from Stony Brook, he builds low-level C++ and runtime components that make ML models run faster across diverse hardware. His background includes production services at Uber and data-quality and ML deployment work at Goldman Sachs, showing a knack for translating business problems into efficient technical solutions. An active contributor to the high-profile microsoft/onnxruntime project, he has improved FP16 model testing and extended DML execution provider operator support. Sumit’s moto—“Make AI run faster, faster and faster”—drives a pragmatic focus on performance portability and scalable inference. Based in Bellevue, WA, he blends systems-level expertise with practical experience in distributed cloud and NLP transformer workloads.
6 years of coding experience
3 years of employment as a software developer
Master of Science - MS, Computer Science, 3.83/4.0, Master of Science - MS, Computer Science, 3.83/4.0 at Stony Brook UniversityAISSCE PCM XII, Physics Chemistry Maths, 90.4%, AISSCE PCM XII, Physics Chemistry Maths, 90.4% at DELHI PUBLIC SCHOOL BOKAROBachelor of Engineering (B.E.), Computer Science, 8.15/10.0 (Absolute Grading), Bachelor of Engineering (B.E.), Computer Science, 8.15/10.0 (Absolute Grading) at Birla Institute of Technology
English, Hindi, Marwari, Sanskrit
Github Skills (8)
machine-learning10
c-language10
deep-learning10
onnx10
cprogramming-language10
hardware-acceleration9
tensorflow7
pytorch7
Programming languages (3)
Github contributions (5)
microsoft/onnxruntime
Apr 2021 - Jan 2023
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Role in this project:
ML Engineer
ML EngineerContributions:313 reviews, 123 commits, 103 PRs in 1 year 9 months
Contributions summary:Sumit contributed to the testing and optimization of ONNX Runtime, specifically focusing on machine learning model inference and execution. They enabled and updated tests for the `fp16_inception_v1` model on various hardware platforms, modifying code related to test tolerance and device-specific configurations. The user also addressed issues with output tensor shape validation between ONNX inference and ONNX Runtime. In addition, the user worked on enhancing DML Execution Provider, including adding support for different versions of Softmax, Hardmax and LogSoftmax operator.
runtimetrainingtensorflowai-frameworkaccelerator
sumitsays/onnxruntime
Mar 2021 - May 2021
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Contributions:4 PRs, 15 pushes, 1 branch in 1 month
pytorchdeep-learningruntimemachine-learningonnx
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