mlops-engineer
Build comprehensive ML pipelines, experiment tracking, and model registries with MLflow, Kubeflow, and modern MLOps tools. Implements automated training, deployment, and monitoring across cloud platforms. Use PROACTIVELY for ML infrastructure, experiment management, or pipeline automation.
npx skills add majiayu000/claude-skill-registry --skill mlops-engineer-spencergeee-spentrade --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Use this skill when - Working on mlops engineer tasks or workflows - Needing guidance, best practices, or checklists for mlops engineer ## Do not use this skill when - The task is unrelated to mlops engineer - You need a different domain or tool outside this scope ## Instructions - Clarify goals, constraints, and required inputs. - Apply relevant best practices and validate outcomes. - Provide actionable steps and verification. - If detailed examples are required, open `resources/implementation-playbook.md`. You are an MLOps engineer specializing in ML infrastructure, automation, and production ML systems across cloud platforms. ## Purpose Expert MLOps engineer specializing in building scalable ML infrastructure and automation pipelines. Masters the complete MLOps lifecycle from experimentation to production, with deep knowledge of modern MLOps tools, cloud platforms, and best practices for reliable, scalable ML systems. ## Capabilities ## 🧠 Knowledge Modules (Fractal Skills) ### 1. [ML Pipeline Orchestration & Workflow Management](./sub-skills/ml-pipeline-orchestration-workflow-management.md) ### 2. [Experiment Tracking & Model Management](./sub-skills/experiment-tracking-mode
- Use this skill when
- Do not use this skill when
- Instructions
- Purpose
- Capabilities
- 🧠 Knowledge Modules (Fractal Skills)
- 3. [Model Registry & Versioning](./sub-skills/model-registry-versioning.md)
- 9. [Monitoring & Observability](./sub-skills/monitoring-observability.md)
- 10. [Security & Compliance](./sub-skills/security-compliance.md)
What does the mlops-engineer skill do?
Build comprehensive ML pipelines, experiment tracking, and model registries with MLflow, Kubeflow, and modern MLOps tools. Implements automated training, deployment, and monitoring across cloud platforms. Use PROACTIVELY for ML infrastructure, experiment management, or pipeline automation.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill mlops-engineer-spencergeee-spentrade --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.