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Description
Work with an experienced ML engineer to build the skills needed to take AI from prototype to production, reliably and at scale. Possible uses of coaching sessions, but not limited to: - ML model deployment and serving infrastructure - Experiment tracking and model versioning tools - Automated deployment pipelines for machine learning - Model monitoring, drift detection, and alerting - Feature store design and data pipeline automation - Cost optimization and inference efficiency at scale - AI code review on your production ML systems
What you'll get from this package
A clear understanding of the MLOps lifecycle from experiment tracking to production monitoring
Hands-on knowledge of key tools and platforms used by ML engineering teams
The ability to design monitoring systems that catch model and data issues early
Skills to build and maintain production ML systems independently
Additional details
Coaching delivered via live sessions and .
Services included:
Technical Skills
AI Research
Model Development
ML Ops & Deployment
AI Code Review
Talk to a team member
Schedule a call with a Leland team member who can help you explore your options.
Schedule a call
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Joined September 2026
4.81
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