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Found 48 Skills
End-to-end data science and ML engineering workflows: problem framing, data/EDA, feature engineering (feature stores), modelling, evaluation/reporting, plus SQL transformations with SQLMesh. Use for dataset exploration, feature design, model selection, metrics and slice analysis, model cards/eval reports, experiment reproducibility, and production handoff (monitoring and retraining).
Machine learning development patterns, model training, evaluation, and deployment. Use when building ML pipelines, training models, feature engineering, model evaluation, or deploying ML systems to production.
Gpu Resource Optimizer - Auto-activating skill for ML Deployment. Triggers on: gpu resource optimizer, gpu resource optimizer Part of the ML Deployment skill category.
Triton Inference Config - Auto-activating skill for ML Deployment. Triggers on: triton inference config, triton inference config Part of the ML Deployment skill category.
Model Registry Manager - Auto-activating skill for ML Deployment. Triggers on: model registry manager, model registry manager Part of the ML Deployment skill category.
Feature Store Connector - Auto-activating skill for ML Deployment. Triggers on: feature store connector, feature store connector Part of the ML Deployment skill category.
NannyML integration. Manage data, records, and automate workflows. Use when the user wants to interact with NannyML data.
Azure Ml Deployer - Auto-activating skill for ML Deployment. Triggers on: azure ml deployer, azure ml deployer Part of the ML Deployment skill category.
Model Export Helper - Auto-activating skill for ML Deployment. Triggers on: model export helper, model export helper Part of the ML Deployment skill category.
You are an **AI Engineer**, an expert AI/ML engineer specializing in machine learning model development, deployment, and integration into production systems. You focus on building intelligent featu...
End-to-end methodology for AI agents and software engineers to add machine learning algorithms to existing non-ML codebases. Covers problem framing, data readiness, architectural decoupling, and baseline model integration.
Onnx Converter - Auto-activating skill for ML Deployment. Triggers on: onnx converter, onnx converter Part of the ML Deployment skill category.