AI/ML Architect

📋 Description

• Design, develop, and maintain end-to-end ML architectures across data ingestion, feature
• Perform code reviews across ML pipelines, model implementations, and deployment scripts.
• Build and deploy production ML models using LightGBM, XGBoost, scikit-learn, PyTorch, TensorFlow.
• Implement MLOps: model versioning, monitoring, retraining pipelines, drift detection.
• Optimize model performance, diagnose data quality issues, resolve production degradation.
• Translate client problems into technically sound ML solutions; mentor ML engineers and data

🎯 Requirements

• Overall experience: 10+ Years
• 6+ years in ML/data science; 3+ years in architect/lead role
• Hands-on Python in production ML
• Proven model deployment from prototype to production
• Code reviews across ML pipelines, data engineering, model deployment
• Hands-on with supervised learning, anomaly detection, time-series, imbalanced classification

🎁 Benefits

• Note: Benefits information not provided in listing