Senior Ml Engineer - Production Pipelines & Mlops

Requirements
Python-based ML development (production ML pipelines & models)
ML frameworks: Scikit-learn, XGBoost/Light GBM/CatBoost, and PyTorch or TensorFlow
Feature engineering & feature pipelines (large-scale, automated where applicable)
Big data processing: Apache Spark / PySpark, Databricks, Delta Lake
MLOps: MLflow (experiment tracking, model registry), model versioning, retraining pipelines
Deployment & Ops: Docker, Kubernetes, REST APIs (FastAPI/Flask), CI/CD and cloud ML services (AWS/Azure/GCP)
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