Machine Learning Engineer


Skills:
🔹 ML Engineering & MLOps
• Productionize ML models using MLflow for experiment tracking, model registry, and lifecycle management
• Implement CI/CD pipelines for ML workflows
• Monitor model performance and manage version control
• Ensure reproducibility and governance of ML assets
• Manage feature pipelines and model retraining strategies
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🔹 Databricks & Distributed Processing
• Build scalable data pipelines using Databricks (Spark)
• Optimize distributed workloads for performance and cost efficiency
• Implement notebook-based and production-grade job workflows
• Leverage Unity Catalog for governance, lineage, and secure data/model access control