MLE Path
Join MLE Path, the podcast that explores what it truly means to grow and thrive as a machine learning engineer.
Hosted by an industry veteran with over 14 years of experience—including leadership roles at Adobe, Twitter, and Meta—this podcast brings you candid conversations with senior ML engineers at the forefront of the field. Together, we uncover the skills, strategies, and insights that define excellence in machine learning engineering at every career stage.
From navigating technical challenges to mastering leadership and innovation, MLE Path provides actionable advice and thought-provoking discussions to help you elevate your career, whether you’re a rising ML engineer or a seasoned professional.
This is your guide to continuous growth and impact in the ever-evolving world of machine learning.
Latest episodes
10 snips
Feb 17, 2025 • 60min
Valerii Babushkin - Mastering ML Careers & System Design
Valerii Babushkin, Senior Director at BP and former Meta E7, shares his wealth of experience in navigating career transitions in tech. He discusses the importance of ambition and curiosity in achieving growth, and the balance between technical skills and management roles. Valerii emphasizes effective communication and documentation in engineering, along with the significance of selecting the right metrics in ML system design. He also sheds light on the value of Kaggle competitions for career development and what differentiates engineers at various levels.
Feb 11, 2025 • 59min
Ville Tuulos - The Art of Machine Learning Timing, Tools, and User Empathy
In this episode, we sit down with Ville Tuulos, CEO of Outer Bounds and creator of Metaflow, to discuss why machine learning is so hard—and how to make it easier. Ville shares his journey from training neural networks at 13 to leading ML infrastructure at Netflix, where he built tools to empower data scientists. We dive into ML cycles, user empathy, infrastructure, and what separates great ML engineers from the rest. 📚 Learn More About Ville Tuulos & Metaflow - Ville Tuulos on LinkedIn: https://www.linkedin.com/in/villetuulos/ - Outer Bounds: https://outerbounds.com - Effective Data Science Infrastructure: How to Make Data Scientists Productive (Ville’s book): https://amzn.to/4hN0Yee (affiliate link)
Feb 3, 2025 • 1h 16min
Kevin Van Horn - Following Jaynes and Why Fundamentals Matter
Dr. Kevin S. Van Horn joins the podcast to discuss Bayesian probability, ML optimization, and lessons from his career. He shares insights on NP-hard problems in ML, Bayesian methods, and how to ensure success in ML projects.
Resources & Links:
Kevin’s Newsletter: https://epistemicprobability.substack.com/ Jaynes' Book on Bayesian Probability: https://amzn.to/42GFOKu
Jan 26, 2025 • 1h 1min
Rebecca Bilbro - Open source, entrepreneurship, and 14 years in ML
Dr. Rebecca Bilbro shares her unique journey through data science and machine learning. We explore the value of blending unusual skill sets, fostering collaboration, and maintaining control in her career.
Rebecca also reflects on her transition from an individual contributor to an entrepreneur, the importance of building strong teams, and the transformative role of open source in the industry.
She offers insights into what makes a great machine learning engineer, the challenges of entrepreneurship, and the critical role of contributor energy in open source projects. We also discuss optimizing machine learning workflows, effective communication in managing ML projects, navigating the hype around ML technologies, and fostering community engagement and transparency in the field.
Links:
LinkedIN
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Applied Text Analysis with Python (affiliate link)
