Senior Ml Engineer

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

作者 alirezarezvani19392f7a0826無授權條款27K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫5 週前更新

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.

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路徑大小類型
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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來源:alirezarezvani/claude-skills位於engineering-team/skills/senior-ml-engineer提交19392f7

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