● Developed APIs integrated with AI/ Neural-Networks pipeline with Django REST.
● Created python tasks/pipelines with Redis and Docker to extract data from AI models and transform the data for APIs integration to separate CPU and GPU pre-processing and post-processing.
● Minimize timeout issues of APIs to 50% by developing APIs with background task scheduler and crons for processing.
● Worked on the database-schemas to improve the time and space complexity. Used TimescaleDB to make databases more efficient in real time analysis up to 40%.
Worked on the pre-processing and post-processing scripts for NLP based ETL pipeline using python.
● Improve the efficiency of scripts by up to 30% by implementing the Spark for the data frames related operations.
● Worked on the Python-based backend components, REST API’s using Django REST Framework, microservices and integrated using Docker.
● Improve the time efficiency up to 40% of local testing by creating microservice to store as well reuse the AI - server results in local, and increase the AI-server optimization.
Worked on optimization and scaling of existing Django Based Web-Application by optimizing the Database schemas and architecture up to 20%.
● Worked on the integrations of various asynchronous Python based microservices using Redis, Celery, Docker.
● Worked on the creating the data pipelines in the DAG and reduce the sync scheduling issues between various microservices up to 30%.
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