Jasper Gilley
About Jasper Gilley
Jasper Gilley is a Machine Learning Engineer currently employed at Ladder, where he has worked since 2024. He has a diverse background in software engineering and machine learning, with experience at several companies and a Bachelor's degree in Computer Science from Northwestern University.
Work at Ladder
Jasper Gilley has been employed at Ladder as a Machine Learning Engineer since 2024. In this role, he focuses on developing and implementing machine learning models to enhance the company's offerings. His tenure at Ladder has lasted for 8 months, during which he has contributed to various projects aimed at improving data-driven decision-making processes.
Previous Experience in Machine Learning
Before joining Ladder, Jasper Gilley worked as a Machine Learning Engineer at Replicate from 2022 to 2023 for 4 months. His experience in machine learning also includes a position as a Football Machine Learning Engineer at Northwestern University from 2017 to 2018, where he applied machine learning techniques to sports analytics.
Software Engineering Background
Jasper Gilley has a solid background in software engineering, having worked in various capacities across multiple organizations. He served as a Software Engineer at Constellation for 2 months in 2019, at Relativity for 2 months in 2020, and at Snapdocs for 1 year from 2021 to 2022. Additionally, he spent 3 years at Propeller Industries, where he worked as a Software Engineer from 2018 to 2021 and previously as a Software Engineering Intern in 2018 for 2 months.
Consulting Experience
Since 2022, Jasper Gilley has been providing AI and machine learning consulting services to various companies. His consulting work is based in San Francisco, California, and spans a period of 2 years. This experience allows him to apply his expertise in machine learning to diverse projects and challenges faced by different organizations.
Education and Qualifications
Jasper Gilley earned a Bachelor's degree in Computer Science from Northwestern University. His education has provided him with a strong foundation in computer science principles, which he has applied throughout his career in both software engineering and machine learning roles.