Found Description
- Must Have: Python‑based ML development (production ML pipelines & models)
- ML frameworks: Scikit‑learn, XGBoost/Light GBM/Cat Boost, and Py Torch or Tensor Flow
- Feature engineering & feature pipelines (large‑scale, automated where applicable)
- Big data processing: Apache Spark / Py Spark, Databricks, Delta Lake
- MLOps: MLflow (experiment tracking, model registry), model versioning, retraining pipelines
- Deployment & Ops: Docker, Kubernetes, REST APIs (Fast API/Flask), CI/CD and cloud ML services (AWS/Azure/GCP)
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