Aasheesh Singh
Senior Research Engineer at Quantiphi
Old Toronto, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolAasheesh Singh is a Senior Research Engineer with nine years of experience bridging academic research and production ML, currently focused on hyper-efficient LLM inference and compression at Quantiphi. He holds advanced training from MILA/Université de Montréal and McGill, and has a strong track record shipping end-to-end systems—from on-device federated learning and mobile recommendation engines to production text-to-animation pipelines and ML microservices. Uniquely, he contributes to low-level ML infrastructure in Rust (notably additions to the burn deep-learning framework: tensor ops, SwiGLU/RMSNorm, rotary embeddings and dataset pipelines), combining systems-level efficiency with applied LLM research. His background spans robotics, autonomous navigation, and HCI, giving him a rare mix of signal-processing, control, and ML modeling expertise that he applies to practical, scalable solutions.
10 years of coding experience
7 years of employment as a software developer
High School, PCM with Computer Science, High School, PCM with Computer Science at Vijaya Sr. Sec. SchoolMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at Mila - Quebec Artificial Intelligence InstituteMaster's degree, Computer Science, 4.0/4.0, Master's degree, Computer Science, 4.0/4.0 at McGill UniversityMaster of Science - MS, Computer Science, 4.12/4.3, Master of Science - MS, Computer Science, 4.12/4.3 at Université de MontréalBachelor of Technology, Electrical, Electronics and Communications Engineering, 8.5/10, Bachelor of Technology, Electrical, Electronics and Communications Engineering, 8.5/10 at Delhi Technological University (Formerly DCE)
English, Hindi, French
Stackoverflow
1reputation
0reached
0answers
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Github Skills (12)
neural-network10
auto-tuning10
autodiff10
machine-learning10
rust10
tensor10
deep-learning10
interpolation9
transformer9
data-loading9
concurrency8
ndarray8
Programming languages (4)
Github contributions (5)
tracel-ai/burn
Jan 2024 - Apr 2024
Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
Role in this project:
ML Engineer
ML EngineerContributions:4 reviews, 11 PRs, 29 pushes in 2 months
Contributions summary:Aasheesh contributed significantly to the `burn` repository, a deep learning framework written in Rust. Their work included implementing dataset loading and batching for a regression example using a Hugging Face dataset. They added support for Any and All operations to the Tensor API and integrated autodiff and training capabilities for nearest neighbor interpolation. Furthermore, they added support for SwiGLU and RMS norm layers and also added rotary positional encoding to the transformer modules.
deep-learningtensorautodiffmachine-learningrust
ashdtu/flower
Jul 2023 - Jan 2024
Flower: A Friendly Federated Learning Framework
Contributions:4 PRs, 40 pushes, 3 branches in 6 months
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