Sayeh Sharify
About Sayeh Sharify
Sayeh Sharify is a Machine Learning Research Engineer and member of the technical staff at Cerebras Systems in Toronto, Ontario, Canada. With a Ph.D. in Computer Engineering from the University of Toronto, she has extensive experience in machine learning, computer architecture, and deep learning, and co-founded Tartan AI.
Work at Cerebras Systems
Currently, Sayeh Sharify serves as a Machine Learning Research Engineer and Member of Technical Staff at Cerebras Systems. She has held this position since 2021, contributing to the company's advancements in machine learning technologies. Her role involves applying her expertise in computer architecture and deep learning to develop innovative solutions in the field.
Education and Expertise
Sayeh Sharify earned her Doctor of Philosophy (Ph.D.) in Computer Engineering from the University of Toronto, completing her studies from 2015 to 2020. She also holds a Master of Applied Science (MASc) in Electrical and Computer Engineering from the same institution, where she achieved a GPA of 3.86/4. Earlier, she obtained a Bachelor of Applied Science (BASc) in Computer Engineering from Sharif University of Technology. Her educational background supports her expertise in designing accelerators for machine learning algorithms.
Background
Sayeh Sharify has a diverse professional background that includes significant roles in academia and industry. Prior to her current position, she worked as a Senior Machine Learning Engineer at Qualcomm from 2020 to 2021. She also gained experience as a Postgraduate Affiliate at the Vector Institute from 2019 to 2021 and as a Research Assistant during her Ph.D. studies at the University of Toronto. Additionally, she interned as a Machine Learning Engineer at Intel Corporation in 2018.
Achievements
In addition to her work at Cerebras Systems, Sayeh Sharify co-founded Tartan AI in 2019, focusing on advancing artificial intelligence technologies. Her involvement in both academic and industry settings highlights her commitment to innovation in machine learning. Throughout her career, she has developed strong programming skills in languages such as C/C++ and Python, which are essential for her research and engineering work.
Teaching Experience
Sayeh Sharify has a solid teaching background, having worked at the University of Toronto from 2014 to 2019. During this five-year period, she gained valuable experience in educating students in various aspects of computer engineering and machine learning, contributing to the academic community.