Vlad Getselevich
Senior Conversational AI Researcher
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolVlad Getselevich is a Research Scientist in AI with a decade of experience specializing in conversational AI and practical NLP engineering. At Nvidia he contributes to the prominent NeMo framework, adapting datasets to the NeMo format and building error analysis and evaluation utilities for intent and slot inference. He combines research-oriented rigor with a pragmatic engineering focus—refactoring code and improving preprocessing pipelines to make experiments more reproducible and production-friendly. Colleagues would note his knack for turning messy annotation schemas into clean, maintainable inputs that accelerate both model development and debugging.
11 years of coding experience
14 years of employment as a software developer
Technion - Israel Institute of Technology
English, Hebrew, Russian, Spanish
Github Skills (12)
data-preprocessing10
machine-learning10
nlp10
deeplearning10
neural-networks10
large-language-models10
python10
generative-ai10
large-language-model10
pytorch9
tensorflow9
tensorflow29
Programming languages (2)
Github contributions (5)
NVIDIA/NeMo
Apr 2020 - Mar 2021
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
Role in this project:
ML Engineer
ML EngineerContributions:39 reviews, 29 commits, 40 PRs in 11 months
Contributions summary:Vlad's commits primarily focus on adapting a new dataset to the Nemo format and incorporating error analysis for intent and slot inference within the NVIDIA Nemo framework. They implemented the `process_assistant` function within the `examples/nlp/intent_detection_slot_tagging` directory, demonstrating expertise in data preprocessing and transformation for NLP tasks. The contributions involve refactoring code, creating utility files for evaluation, and minor variable renaming, indicating a focus on code maintainability and organization within the Nemo framework.
asrspeech-recognitionnatural-language-processingttsspeaker-diarization
vladgets/NeMo
Mar 2020 - Jun 2020
Neural Modules: a toolkit for conversational AI
Contributions:11 pushes, 5 branches in 3 months
nlpconversationalconversational-aimachine-learningchatbot
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