- Design, implement, and manage end-to-end machine learning pipelines to streamline model training, evaluation, and deployment.- Oversee data preprocessing and batch processing pipelines, ensuring data quality and efficient handling for inference.- Set up and maintain scalable, secure AWS environments to support machine learning workloads, using Sagemaker, EC2, Lambda, S3, and other AWS services.- Deploy models to production and build monitoring systems for performance tracking and logging, optimizing models for operational use.- Partner with ML engineers, and the GIS team to align and enhance technical workflows with Farmevo’s mission, driving innovative solutions tailored to the agriculture sector.

-I presently have the responsibility of creating and designing user interfaces in my capacity as an intern web developer. I was in charge of handling API data and converting it to UI in my projects at DLS.-After completing my first assignment, I am currently working on the product, where my responsibility is to enhance the most recent version that is currently available and address any problems that emerged during UAT. The system will also get a fresh front-end functionality.-I've been able to advance both professionally and personally by having the chance to work on projects both independently and under the guidance of seniors.