Abhishree Thittenamane
Deep Learning Engineer at NVIDIA
Austin, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolAbhishree Thittenamane is a Deep Learning Engineer with 5 years of experience applying machine learning and computer vision to real-world systems, currently building models and tooling at NVIDIA after driving DNN performance optimization across AMD GPUs. With an MS in Electrical and Computer Engineering from the University of Minnesota and a strong signal-processing background from internships in medical devices and embedded systems, she bridges low-level performance tuning and high-level model design. Her work spans CV and NLP acceleration, sensor-fusion time-series modeling, and teaching robot vision, showing an unusual blend of firmware-level testing, algorithm development, and deployment-focused optimization. Based in California, she combines rigorous academic training and production GPU experience to squeeze efficiency out of modern deep networks while keeping models practical for deployment.
5 years of coding experience
5 years of employment as a software developer
Schooling, CBSE, 94%, Schooling, CBSE, 94% at Jnanadeepa School, Shimoga, KarnatakaBachelor’s Degree, Electrical, Electronics and Communications Engineering, 9.51, Bachelor’s Degree, Electrical, Electronics and Communications Engineering, 9.51 at Ramaiah Institute Of TechnologyPre University, 95%, Pre University, 95% at Sri Aurobindo Pre University College, Shimoga, KarnatakaUniversity of Minnesota Twin Cities
English, Kannada, Hindi
Github Skills (42)
speaker-diarization10
speech-to-text10
machine-translation10
language-model10
python10
machine-learning10
speech-synthesis10
multimodal10
pytorch-lightning10
text-normalization10
nmt10
large-language-models10
temporal-data10
deep-learning10
gpu10
Programming languages (1)
Github contributions (5)
athitten/training_results_v0.7
Dec 2020 - Mar 2022
Contributions:2 pushes, 1 branch in 1 year 3 months
athitten/pytorch-lightning
Jan 2024 - Feb 2024
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
Contributions:2 pushes, 2 branches in 1 month
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