senior-ml-engineer

Malicious tool definition detected

Tool: SKILL.md [1/2] Description: --- name: senior-ml-engineer description: ML engineering skill for productionizing models, building MLOps pipelines, and integrating LLMs. Covers model deployment, feature stores, drift monitoring, RAG systems, and cost optimization.

Tool: SKILL.md [2/2] Description: - Provider abstraction layer pattern - Retry and fallback strategies with tenacity - Prompt engineering templates (few-shot, CoT) - Token optimization with tiktoken - Cost calculation and tracking ### RAG System Architecture `references/rag_system_architecture.md` contains: - RAG pipeline implementation with code - Vector database comparison and integration - Chunking strategies (fixed, semantic, recursive) - Embedding model selection guide - Hybrid search and r

Malicious tool definition detected

Tool: references/llm_integration_guide.md Description: # LLM Integration Guide Production patterns for integrating Large Language Models into applications.

Malicious tool definition detected

Tool: references/mlops_production_patterns.md Description: # MLOps Production Patterns Production ML infrastructure patterns for model deployment, monitoring, and lifecycle management. --- ## Table of Contents - [Model Deployment Pipeline](#model-deployment-pipeline) - [Feature Store Architecture](#feature-store-architecture) - [Model Monitoring](#model-monitoring) - [A/B Testing Infrastructure](#ab-testing-infrastructure) - [Automated Retraining](#automated-retraining) --- ## Model Deployment P

Malicious tool definition detected

Tool: references/rag_system_architecture.md [1/2] Description: # RAG System Architecture Retrieval-Augmented Generation patterns for production applications.

Tool: references/rag_system_architecture.md [2/2] Description: results] scores = self.model.predict(pairs) # Update scores and sort for i, score in enumerate(scores): results[i].score = float(score) return sorted(results, key=lambda x: x.score, reverse=True)[:top_k] ``` ### Query Expansion ```python def expand_query(query: str, llm: LLMProvider) -> List[str]: """Generate query variations for better retrieval.""" prompt = f"""Generate 3 alternative phrasings of this question for search.

Malicious tool definition detected

Tool: scripts/ml_monitoring_suite.py Description: #!/usr/bin/env python3 """ Ml Monitoring Suite Production-grade tool for senior ml/ai engineer """ import os import sys import json import logging import argparse from pathlib import Path from typing import Dict, List, Optional from datetime import datetime logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s' ) logger = logging.getLogger(__name__) class MlMonitoringSuite: """Production-grade ml monitoring su

Malicious tool definition detected

Tool: scripts/model_deployment_pipeline.py Description: #!/usr/bin/env python3 """ Model Deployment Pipeline Production-grade tool for senior ml/ai engineer """ import os import sys import json import logging import argparse from pathlib import Path from typing import Dict, List, Optional from datetime import datetime logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s' ) logger = logging.getLogger(__name__) class ModelDeploymentPipeline: """Production-grad

Malicious tool definition detected

Tool: scripts/rag_system_builder.py Description: #!/usr/bin/env python3 """ Rag System Builder Production-grade tool for senior ml/ai engineer """ import os import sys import json import logging import argparse from pathlib import Path from typing import Dict, List, Optional from datetime import datetime logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s' ) logger = logging.getLogger(__name__) class RagSystemBuilder: """Production-grade rag system builder"