Why 90% of ML Engineers Struggle in Real-World Systems

Most ML engineers don’t fail because they lack knowledge. They fail because they’re solving the wrong problem. 🚨 The Hard Truth Most ML engineers are trained to: Optimize models Improve accuracy Tune hyperparameters But real-world systems don’t fail because of bad models. They fail because of: Bad system design 🧠 The Root Problem ML education focuses on: Dataset → Model → Accuracy But real-world systems look like: Data → Pipeline → System → Monitoring → Feedback → Iteration 👉 The model is jus