Python Developer and ML

 Build and maintain ML model serving APIs using FastAPI or Flask.
• Implement asynchronous Python services and integrate with REST/gRPC APIs.
• Utilize ML tooling for experiment tracking, model versioning, and monitoring (MLflow, Weights & Biases, ClearML, or similar).
• Work with Docker and basic Kubernetes for containerized ML deployments.
• Integrate ML workflows into CI/CD pipelines for automated deployment and testing.
• Collaborate with data engineers to design and optimize data pipelines for ML workloads.
• Write efficient SQL queries and work with relational/columnar databases like PostgreSQL, ClickHouse, or BigQuery.
• Use Git for version control and implement unit and integration tests using pytest.