Tech

As a Machine Learning Engineer in Adobe Document Cloud, I worked on a variety of products in Adobe Acrobat, Adobe Sign, and Adobe Express.

Patents

Model-based semantic text searching

Machine-learning tool for generating segmantation and topic metadata for documents

Publications

SemEval-2020 Task 6: Definition Extraction from Free Text with the DEFT Corpus

DEFT: a corpus for definition extraction in free- and semi-structured text

• Architected, implemented, and deployed inference and evaluation libraries for state-of-the-art machine learning models

• Built data visualization pipelines for quantitative and qualitative error analysis

• Used software engineering and linguistics techniques to speed up PyTorch inference code by 10x, reducing compute cost by 80x

• Optimized AWS Athena queries to run 2x faster while also making the queries more readable and maintainable

• Developed engineering team guidelines to emphasize psychological safety and strong engineering practices

• Led group workshops and individual trainings on computational linguistics, natural language processing, and full-stack web development

Engineering

• Applied and introduced user research and usability testing techniques to multiple internal and external features, from ideation and concept validation to 100% rollout

• Used full-stack web app libraries and design systems to build interactive prototypes for concept validation and usability testing

• Implemented and adapted qualitative and quantitative techniques to measure customer impact

• Built and maintained lasting relationships across research, product, and engineering orgs

• Led workshops in how qualitative research can help teams anticipate and overcome the pitfalls of large language models and chatbots