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)