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.
data-engineering
Data engineering, machine learning, AI, and MLOps. From data pipelines to production ML systems and LLM applications.
ml-deployment
Deploy ML models to production - APIs, containerization, monitoring, and MLOps
mlops-basics
Master MLOps fundamentals - lifecycle, principles, tools, practices, and organizational adoption
ml-pipeline-workflow
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.
