Senior Ml Engineer

alirezarezvani/claude-skills/engineering-team/skills/senior-ml-engineer

作者 alirezarezvani19392f7a0826无许可证27K 个星标收录于 2026年10月8日更新于 2026年10月8日仓库5周前更新

ML engineering skill for productionizing models, building MLOps pipelines, and integrating LLMs. Covers model deployment, feature stores, drift monitoring, RAG systems, and cost optimization. Use when the user asks about deploying ML models to production, setting up MLOps infrastructure (MLflow, Kubeflow, Kubernetes, Docker), monitoring model performance or drift, building RAG pipelines, or integrating LLM APIs with retry logic and cost controls. Focused on production and operational concerns rather than model research or initial training.

仅公开文件列表。将技能安装到工作区后即可查看文件内容。

路径大小类型
references/llm_integration_guide.md8.7 KBtext/markdown
references/mlops_production_patterns.md7.1 KBtext/markdown
references/rag_system_architecture.md10 KBtext/markdown
scripts/ml_monitoring_suite.py2.7 KBtext/plain
scripts/model_deployment_pipeline.py2.7 KBtext/plain
scripts/rag_system_builder.py2.7 KBtext/plain
SKILL.md9.5 KBtext/markdown

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来源:alirezarezvani/claude-skills位于engineering-team/skills/senior-ml-engineer提交19392f7

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