Arbaaz Qureshi
Applied Scientist at Amazon
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolArbaaz Qureshi is an Applied Scientist with nine years of experience building and evaluating ML systems across industry-leading teams at Amazon, Lowe’s, Google, Microsoft and IBM. He specializes in large language model agents, conversational recommendation systems, and model interpretability—publishing work on neuron-level concept attribution in BERT and practical LLM-driven product discovery features. His background spans applied production ML (off-body detection for Pixel Watch, context-aware query completion) to research-grade multimodal and multi-task deep learning that set state-of-the-art results on depression estimation. With an MS in Computer Science from UMass Amherst and a track record of shipping both research and production systems, he bridges rigorous evaluation and deployable engineering. A not-obvious throughline in his work is combining interpretability and user-facing intelligence to make complex models both effective and accountable in real products.
9 years of coding experience
3 years of employment as a software developer
Bachelor's degree Computer Science and Engineering, Bachelor's degree Computer Science and Engineering at Indian Institute of Technology, PatnaMaster's degree Computer Science, Master's degree Computer Science at University of Massachusetts Amherst
English, Hindi, Urdu, Telugu
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (5)
bugtracking9
textbook6
algorithm6
algorithms4
python1
Programming languages (2)
Github contributions (5)
arbaazQureshi/depression_estimation_from_individual_modalities
Jan 2019 - May 2019
Contributions:4 commits, 2 pushes, 1 branch in 3 months
arbaazQureshi/multitask_learning_on_depression_and_emotion
May 2019 - May 2019
Contributions:3 commits, 1 push, 1 branch in 1 day
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