Simon Lemay
About Simon Lemay
Simon Lemay is a Senior Machine Learning Engineer Lead with extensive experience in software engineering and machine learning. He has held various leadership roles in companies such as Horizon Labs and Borealis AI, contributing to the development of advanced machine learning systems and fostering a high-performing engineering culture.
Current Role at Horizon Labs
Simon Lemay serves as the President of Horizon Labs since 2022. In this role, he oversees operations and strategic direction, leveraging his extensive experience in engineering and technology. His leadership focuses on fostering innovation and driving the development of advanced solutions in the tech industry.
Work at Borealis AI
Simon Lemay is currently a Senior Machine Learning Engineer Lead at Borealis AI, a position he has held since 2022. He plays a key role in transforming prototypes into fully functional solutions for both internal and external applications. His contributions include collaborating with research and business teams to address engineering needs and facilitate the productization of new machine learning systems.
Professional Background
Simon Lemay has over fifteen years of experience in various engineering roles. He has worked at Bluberi, Zebra Technologies, Arm, Taiga Motors, and WMS Gaming. His roles have ranged from Analyst-programmer to Senior Software Engineer and Lead Engineer, with a focus on embedded, mobile, local, and cloud stack technologies. He has held positions that emphasize networking and security, showcasing his versatility in the tech sector.
Education and Expertise
Simon Lemay studied Computer Science at Champlain College, earning a DEC from 2003 to 2006. He also attended École de technologie supérieure and Du Phare. His educational background supports his expertise in machine learning, deep learning, and natural language processing, which he applies in his current and previous roles.
Research Contributions
Simon Lemay has contributed to various research blogs while at Borealis AI. His work includes exploring reinforcement learning from human feedback, speeding up inference in transformers, and mastering language models. He has also published tutorials and contributed to research on neural tangent kernels, demonstrating his commitment to advancing knowledge in machine learning.