Nolan Dey
About Nolan Dey
Nolan Dey is an ML Research Scientist II currently working at Cerebras Systems in Toronto, Ontario, Canada. He has a diverse background in machine learning and software engineering, with previous roles at companies such as Capital One, Apple, and Kik Interactive.
Current Role at Cerebras Systems
Nolan Dey currently serves as an ML Research Scientist II at Cerebras Systems, a position he has held since 2022. He works in Toronto, Ontario, Canada, focusing on advancing machine learning technologies. His role involves leveraging his expertise in machine learning frameworks and cloud infrastructure to contribute to the company's innovative projects.
Previous Experience at Cerebras Systems
Before his current position, Nolan worked at Cerebras Systems as an ML Research Scientist I from 2021 to 2022. During this year-long tenure, he contributed to various machine learning initiatives, applying his knowledge in frameworks such as PyTorch and TensorFlow to enhance the company's research capabilities.
Educational Background
Nolan Dey studied at the University of Waterloo, where he earned a Master of Applied Science (MASc) in Systems Design Engineering from 2019 to 2021. He also completed his Bachelor of Applied Science (BASc) in the same field from 2014 to 2019. Additionally, he participated in an Engineering Exchange Semester at Lund University in 2018.
Internship Experience
Nolan has a diverse internship background, having worked in various roles that enhanced his skills in machine learning and software engineering. He was a Data Science Intern at Capital One in 2017, a Machine Learning & Web Intern at Apple, and held multiple positions at Kik Interactive, including Quality Assurance Engineering Intern and iOS Developer Intern in 2015. His experience also includes roles as a Full-Stack Developer Intern at Parabol and a Machine Learning Research Intern at Mind Foundry.
Technical Skills and Expertise
Nolan possesses expertise in a wide range of machine learning frameworks and libraries, including PyTorch, Jax, TensorFlow, and Nengo. He has extensive experience with cloud infrastructure platforms such as GCP and AWS, along with containerization tools like Docker. His skill set also includes data visualization and analysis tools like MatPlotLib and Pandas, infrastructure automation tools like Terraform, and orchestration systems like SLURM. He is proficient in programming languages and frameworks such as Node, React, and Scala, and has experience in database management with PostgreSQL and MongoDB.