• Contributing to the ideation, design and development of an integrated platform aimed at simplifying and standardizing AI, ML, DL and LLM workflows

• Collaborating with cross-functional teams to design features that cater to data scientists, data engineers, and end-users looking to easily run inference on existing models or train and fine-tune new models

• Own and actively maintain 7 critical banking microservices across the stack on PNC's Lending Platform.

• Consistently closed 8+ feature tickets per week, ensuring reliability on a senior-heavy team.

• Mentored a new hire cohort of senior engineers, cultivating a collaborative team atmosphere within a dynamic and fast-paced environment.

• Deploy production-ready code weekly using Docker and Jenkins; contribute to agile sprints and team code quality through reviews

• Enhanced performance and user experience across 30+ diverse services and APIs, supporting the migration and enhancement of customer-facing applications on LPL's Risk & Regulatory platform.

• Designed and implemented structured training programs for three new engineers, enhancing their time-to-competency by 50% and ensuring their effective integration into project workflows.

• Spearheaded a collaborative sub-team in an innovative machine learning project aimed at enhancing lab safety, resulting in high accuracy.

• Built and trained computer vision models (instance classification, semantic segmentation) to detect PPE compliance for lab scientists in pharmaceutical research.

• Improved lab safety monitoring with a scalable model that achieved approximately 80% accuracy and could be deployed across multiple environments.

• Trained the Pytorch model on 10,000+ images scraped using Selenium and pre-processed using Roboflow, and openCV.