Jofia Jose Prakash
About Jofia Jose Prakash
Jofia Jose Prakash is an Artificial Intelligence Engineer currently employed at the American Chemical Society, where he has worked since 2019. He has a diverse background in software engineering and application development, with experience at several organizations including Kott Software, Ciber Global, and Hewlett-Packard.
Work at American Chemical Society
Jofia Jose Prakash has been employed at the American Chemical Society as an Artificial Intelligence Engineer since 2019. In this role, Prakash focuses on optimizing machine learning solutions, providing technical leadership in cross-functional teams. The position involves enhancing performance and efficiency in various applications of artificial intelligence within the organization.
Previous Employment History
Before joining the American Chemical Society, Jofia Jose Prakash held several positions in the technology sector. Prakash worked as a Software Engineer at Kott Software Pvt. Ltd. from 2007 to 2008, followed by a role as a Software Engineer at Larsen & Toubro Infotech from 2008 to 2011. Prakash also served as a Technology Consultant at Hewlett-Packard from 2011 to 2013 and as an Application Developer at Ciber Global from 2016 to 2018. Additionally, Prakash was a Graduate Assistant at Oakland University from 2015 to 2016.
Education and Expertise
Jofia Jose Prakash earned a Master’s Degree in Computer Science from Oakland University, completing the program from 2015 to 2016. This academic background provides a strong foundation in artificial intelligence and machine learning. Prakash specializes in the integration of retrieval-augmented generation techniques within large language models and has a solid understanding of reinforcement learning.
Technical Skills and Contributions
In the capacity of an Artificial Intelligence Engineer, Jofia Jose Prakash excels in translating complex business objectives into actionable machine learning strategies. Prakash contributes to the development of scalable machine learning architectures and has a strong foundation in reinforcement learning. This expertise allows for the optimization of machine learning solutions, enhancing both performance and efficiency in various projects.