News

Where: TMCB 1170

When: March 13th, 2025 @ 11:00 AM

Speaker: Mike Jones

Lifecycle of a Machine Learning Product: Conception to Production

Building machine learning products that are both effective and scalable requires more than just model development—it’s about mastering the entire lifecycle, from conception to deployment. In this talk, we’ll break down the essential principles for creating successful ML systems, starting with a deep understanding of the business problem and how the product will provide real value to customers. We’ll discuss best practices, key trade-offs in system design, and how to balance the needs of software development with the demands of machine learning. Finally, we’ll explore how to monitor and maintain deployed systems to ensure they continue to evolve and meet business needs over time.

Join us to learn actionable strategies for building ML products that not only address immediate goals but also grow and scale, delivering lasting business value. For the future professionals in the audience, there will be a little career advice sprinkled throughout the talk as well.

Dr. Mike Jones is an experienced leader and innovator in the field of machine learning, with over 30 years of expertise spanning both academic and industry roles. He earned a B.S. in Computer Science from Brigham Young University and an M.S. and Ph.D. in Computer Science from the University of Colorado at Boulder. Currently serving as Senior Director of Machine Learning (ML) at Proofpoint, Mike oversees a team of data scientists and engineers developing AI-driven products across security, data protection, and compliance. Mike has built and led cutting-edge ML systems at organizations such as Symantec, FamilySearch, and Mobile Productivity, specializing in scalable data pipelines, generative AI, and large-scale machine learning applications. His work has had a significant impact across industries, from security to genealogy, and he has authored several research publications in machine learning and information retrieval. A passionate mentor, Mike fosters the professional development of his teams, shaping the next generation of ML leaders and driving innovative AI research and development initiatives.