Agent skill · security · aiskillstore

senior-ml-engineer

World-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.

Why this skill is useful

Adds 3 executable scripts for model deployment, RAG system building, and ML monitoring that enhance the AI's capabilities in productionizing ML models.

What it needs

Requires docker, kubernetes installed locally. About 3k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.

What this skill does

Senior ML/AI Engineer World-class senior ml/ai engineer skill for production-grade AI/ML/Data systems. Quick Start Main Capabilities Core Expertise This skill covers world-class capabilities in: Advanced production patterns and architectures Scalable system design and implementation Performance optimization at scale MLOps and DataOps best practices Real-time processing and inference Distributed computing frameworks Model deployment and monitoring Security and compliance Cost optimization Team leadership and mentoring Tech Stack Languages: Python, SQL, R, Scala, Go ML Frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost Data Tools: Spark, Airflow, dbt, Kafka, Databricks LLM Frameworks: LangChain, LlamaIndex, DSPy Deployment: Docker, Kubernetes, AWS/GCP/Azure Monitoring: MLflow, Weights & Biases, Prometheus Databases: PostgreSQL, BigQuery, Snowflake, Pinecone Reference Documentation 1. Mlops Production Patterns Comprehensive guide available in references/mlopsproductionpatterns.md covering: Advanced patterns and best practices Production implementation strategies Performance optimization techniques Scalability considerations Security and compliance Real-world case studies 2. Llm Integration Guide Complete workflow documentation in references/llmintegrationguide.md including: Step-by-step processes Architecture design patterns Tool integration guides Performance tuning strategies Troubleshooting procedures 3. …

How to use it

Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:

@skills aiskillstore/senior-ml-engineer--52d378

View the source on GitHub

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