Machine Learning Engineer
hardmachine-learning-engineer-edge-deployment
What changes when deploying ML models on edge devices (mobile/IoT)?
Answer
Edge deployment constraints include limited CPU/GPU, memory, and battery.
You often need:
- Smaller models (distillation)
- Quantization
- On-device caching
- Privacy-safe logging
Measure latency on real devices and plan updates carefully (versioning, rollback, compatibility).
Related Topics
EdgeOptimizationDeployment