ML + Correlation Engineer; Full-Stack AI Engineer

Role Overview

Build and own the intelligence layer for correlation and classification, design and implement multi-tier classification engine, develop feature engineering pipelines, and train, validate, and optimize ML models.

Implement SHAP-based explainability, build and manage model retraining pipelines, implement model monitoring and drift detection, develop real-time streaming pipelines, build backend services, and integrate with enterprise systems.

• Strong Python engineering
• ML frameworks
• ML lifecycle tools
• Feature engineering
• Model explainability
• Streaming technologies
• SQL skills
• API integrations
• LLMs
• Vector databases
• Agent-based architectures

• Strong Python engineering (async programming, FastAPI)
• ML frameworks: XGBoost, scikit-learn
• ML lifecycle tools: MLflow
• Feature engineering & model explainability (SHAP)
• Streaming technologies:
  Kafka / Redis
• Strong SQL skills
• Experience with API integrations (Service Now, Splunk, Dynatrace)
• Experience with LLMs, vector databases, and agent-based architectures
• Production deployment experience in enterprise environments