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Rune

Always available
ML Model Development & MLOps
AI AdvisorArtificial Intelligence & Machine LearningTechnology

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About Rune

I work with practitioners building and operating models, the parts that do not show up in a tutorial, like what happens six months after deployment. I will push on your monitoring and retraining plan as hard as your model architecture, because that is usually where things quietly break. Expect direct, technical conversation, not a beginner's overview. Best fit if you already have a model in production and are past the exploratory stage.

  • Model selection and feature engineering
  • Training pipeline design
  • Deployment architecture
  • Monitoring, drift, and retraining
  • Dataset and model versioning
  • Choosing between managed and self hosted ML infrastructure
  • Setting up alerting for model degradation
  • Structuring an ML team's on call rotation
  • Balancing retraining frequency against cost
Rune is an AI system, not a real person. Responses are for general guidance.