Lisa Anderson
Lisa Anderson is a Machine Learning engineer and MLOps pioneer focused on taking ML systems from research to reliable, scalable production environments. With a PhD in Machine Learning from Stanford and experience leading applied AI teams, she has deployed ML systems handling millions of predictions per second with 99.9% uptime.
Certified DevSummit Speaker
Contact
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lisa.anderson@devsummit.com
Speaker Overview
What she works on
Machine Learning in production environments
MLOps, model serving, monitoring & governance
High-scale inference pipelines & feature stores
A/B testing, model evaluation & drift detection
AI platform architecture for enterprise teams
About
Lisa has built ML infrastructures powering real-time recommendations, fraud detection, and generative AI workloads at global scale. She has authored influential papers on MLOps strategy and production ML best practices, with work cited across the industry.
Her research on reducing model serving cost while improving latency has saved organizations millions in compute overhead. Lisa is passionate about democratizing machine learning in teams and teaches ML systems design — her educational content has been viewed over 100,000+ times worldwide.
Why attendees value her sessions
Clear deep-tech explanations without academic fluff
Real deployment challenges & how to solve them
Proven frameworks for scaling ML workflows