Mikalai Drabovich
AI Engineer at Quadric
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolMikalai Drabovich is an AI Engineer with 11 years of experience building high-performance ML pipelines and numerics for custom hardware, currently working on AI workloads at Quadric. He has deep expertise in LLM workload simulation, handcoded and compiler-generated kernels, microscaling numerical formats, and collective/barrier optimizations from his Sr. Staff role at d-Matrix. At AMD he implemented end-to-end training and inference on AMD-only hardware and developed TensorScope and DeepSpeed-ROCM tooling to pinpoint TFLOPs and memory bottlenecks—skills that combine systems-level profiling with model-aware optimization. His background spans computer vision on mobile devices, research into fixed-precision DNN mappings, and even launching consumer apps with millions of downloads, reflecting a rare mix of low-level hardware-software co-design and product-focused engineering. Based in Palo Alto, he brings practical experience turning numerical research into production-ready ML pipelines on alternative architectures.
10 years of coding experience
15 years of employment as a software developer
Master's Degree Radiophysics and Electronics, Master's Degree Radiophysics and Electronics at Belarusian State UniversityHeriot-Watt University Edinburgh CampusArtificial Intelligence AI, Artificial Intelligence AI at Stanford University
English, Russian, Russian
Stackoverflow
53reputation
6kreached
6answers
0questions
Github Skills (71)
python10
deep-learning10
compression10
ml10
neural-network10
data-science10
tensorflow10
speech-to-text10
mixture-of-experts10
machine-learning10
signature10
deep-neural-networks10
scanner9
dependency-free9
hash9
Programming languages (5)
Github contributions (5)
MikalaiDrabovich/DNA_2_Amino_acids
Jun 2015 - Jan 2022
Contributions:1 push, 1 branch in 6 years 8 months
MikalaiDrabovich/fast-pixel-classification-dnn-caffe
Jul 2017 - Nov 2017
Contributions:1 release, 22 commits, 2 PRs in 3 months
pedestriansreal-time-detectioncarsroadsreal-time
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