From Medicine to Machine Learning: How Public Learning Turned into a Career
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How do you learn machine learning while studying medicine and turn it into a full-time career? - Pastor Soto
In this episode, we’re joined by Pastor Soto, a Machine Learning Engineer who learned ML through focused online learning and consistent public work. While still in medical school, Pastor took on side projects that led him into machine learning, and the ML Zoomcamp course served as a turning point in his career.
By sharing his work online, Pastor opened the door to job interviews, including at Meta and DeepLearning.AI.
We plan to cover:
- How Pastor learned ML while studying medicine
- How ML Zoomcamp helped Pastor to get interviews at companies like Meta and DeepLearning AI
- Lessons for time-constrained learners: small wins, public updates, and ROI
- How to position a non-traditional background (like an MD) in AI interviews
About the speaker:
Pastor Soto is a Machine Learning Engineer and mentor with a practical bias toward shipping. While studying medicine at the university, he took on side work that pulled him into machine learning. The inflection point was ML Zoomcamp: by publishing exercises and projects publicly, he attracted interviews and job offers.
Pastor’s work centers on production ML: moving data, wiring APIs, and feeding LLMs so applications run. He mentors with DeepLearning.AI, leads sections for Stanford’s Code in Place, and writes about focused learning and small, finished steps that compound.
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From Medicine to Machine Learning: How Public Learning Turned into a Career