Implement and scale advanced ML algorithms and incorporate recent advancements in the field to address relevant ML problems
Adapt, customize, or build-upon state-of-the-art AI/machine learning solutions
Build end-to-end data processing pipelines to support large-scale model learning.
Build quick Proof of Concepts (POC) and take ownership around projects to demonstrate utilization and value and drive to production-ready solutions
Collaborate with ML scientists, engineers, and other groups within Mlogica to build and deploy ML solutions

Elicited clients\' requirements thoroughly and efficiently implements them.
Worked in a small team environment and supported team members where needed. 
Designed architectures of the projects and maintained software requirement specification along with the development 

Responsibilities involved requirement study, data cleaning, model building, and testing.
Created and analyzed different architectures of models to achieve good accuracy. Also, Created a backend server using a flask.
Analyzed complex data sets with in-depth statistical analysis to find trends, patterns, and anomalies.