Ml Engineer

This is a comprehensive production ML engineering skill that covers the full stack from PyTorch 2.x and TensorFlow to model serving with TorchServe and TensorFlow Serving. It handles feature stores like Feast, distributed training with DDP and DeepSpeed, and monitoring for drift detection. Use it when you're building actual production ML systems that need to scale, not just training notebooks. The behavioral traits emphasize reliability over complexity, which is the right mindset for production work. It's opinionated about MLOps practices and explicitly considers business metrics alongside technical ones. Heavy on deployment infrastructure like Kubernetes and cloud platforms, lighter on research or exploratory ML.

Install to Claude Code

npx -y skills add sickn33/antigravity-awesome-skills --skill ml-engineer --agent claude-code