Abhir Karande
Encino, Los Angeles
Summary
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SeniorAbhir Karande is a compute performance engineer focused on AI cluster optimization with eight years of experience blending machine learning research and production engineering. Currently at SK hynix America, he works on LLM inference serving and memory-centric compute, building on prior internships and MLOps work at T-Mobile and hands-on ML research at UVA (NSF-funded FloodWatch). He holds an MS in Electrical Engineering & Computer Science from USC and a BS from UVA, and has moved between research and applied roles—bridging simulation, inference optimization, and systems engineering. Based in Malibu, Abhir brings a practical curiosity for hardware-aware software tuning and has contributed to projects that tighten the loop between memory architectures and ML inference performance.
8 years of coding experience
Github Skills (32)
ios9
pytorch9
python9
windows9
tensorflow9
android9
flutter9
jax9
macos9
dart8
cross-platform8
material-design8
machine-learning8
numpy8
mobile8
Programming languages (8)
Github contributions (5)
AbhirKarande/MLsmartExerciseTracker
Apr 2022 - Dec 2022
Contributions:21 commits, 13 pushes, 2 branches in 8 months
AbhirKarande/NAOobjectRecognition
Dec 2018 - Aug 2020
Contributions:14 commits, 13 pushes in 1 year 9 months
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