OpenClaw
senior-ml-engineer
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 ra
2.8k stars
openclaw/skillsskills/alirezarezvani/senior-ml-engineerMarch 14, 2026
Install command
python "$CODEX_HOME/skills/.system/skill-installer/scripts/install-skill-from-github.py" --repo openclaw/skills --path skills/alirezarezvani/senior-ml-engineerTell me the task — I'll narrow the agent shortlist.