TorchServe is a framework for deploying PyTorch models as APIs. Package model + custom handlers, deploy to servers or Kubernetes. TorchServe handles batching, multi-GPU, model versioning, and A/B testing. Teams using TorchServe reduce time-to-production from weeks to days. Senior ML engineers comfortable with TorchServe earn 15-25% premium. Mastery takes 4-6 weeks.
TorchServe is Facebook's framework for deploying PyTorch models as production APIs. You package your model (trained weights), write a handler (preprocessing and postprocessing code), and TorchServe exposes it via REST/gRPC endpoints. TorchServe handles operational concerns: batching (combine 32 requests into one forward pass), GPU management, model versioning, A/B testing, and metrics. This lets ML engineers focus on model quality, not infrastructure.
| ప్రాంతం | జూనియర్ | మధ్య | సీనియర్ |
|---|---|---|---|
| USA | $85k | $140k | $210k |
| UK | £52k | £85k | £130k |
| EU | €58k | €95k | €145k |
| CANADA | C$90k | C$145k | C$220k |
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