Python Developer with Django

- Develop and maintain large-scale data processing pipelines utilizing Apache Spark for both batch and streaming data - Design and execute machine learning training and inference workflows using PyTorch, integrating these into production systems - Create and manage ETL and ML pipelines with Apache Airflow, ensuring they are reliable, scalable, and observable - Enhance the performance of data pipelines and ML model training conducted on distributed clusters - Collaborate with Data Scientists and ML Engineers to transition models into production environments - Apply best practices for code quality, continuous integration/continuous delivery (CI/CD), unit testing, and monitoring - Safeguard data quality, integrity, and security throughout all pipelines - Diagnose performance issues and optimize resource usage - Keep abreast of developments in machine learning frameworks, distributed computing, and workflow orchestration tools