As the lead UI engineer for the LEAP (Labeling and Evaluation of AI Platform), I was responsible for working with our Product team, Customer team, and an international team of specialized Linguists to design and develop a platform for users to evaluate the quality of AI outputs across multiple locales. From establishing the acceptance criteria and developing testing methodology, then following through generating data and analyzing the results, I led the User Experience in both technical design and implementation. With dedication to ensuring a great end user experience, I built a devoted user base and drove adoption across multiple product lines. This was a key highlight of our AI initiative and used to make strategic decisions about product ramps and releases, training future versions of LLMs, and in the process reduced the per-interaction evaluation time by 40%, allowing us to evaluate more data with the same number of evaluators. As the UI Tech Lead for the internal taxonomy tools, I owned and drove progress for a taxonomy data management application that powers the search and classification of LinkedIn’s core Member derived datasets using Ember.js. I created and managed the project lifecycle for multiple UI microservices frontends for managing internal tools and projects. I applied my excellent time management and organizational skills to manage multiple small projects, including setting and meeting timelines, coordinating with client teams to set expectations, and mentoring junior engineers beginning software development careers in code quality and collaborating with clients while meeting the demands of Product Management teams.

I worked to create and refine data visualizations for large, complex data sets such as computer networks, as well as filtering and analyzing the resulting data. I focused on improving user-intuitive workflows, scaling to ever-larger data sets and improving performance, and using data visualization to illuminate and solve network security problems.

Protein Analytical Chemistry at Genentech SSF location.Development of scripts (python) for analysis of complex data sets from peptide map mass spectrometry, as well as web applications (JavaScript) to assist with scientific calculations. Method development for various bio-analytical assays, including SEC, IEC, HIC, RP-HPLC/MS, method validation, protein characterization, imaged capillary electrophoresis, sequence variant analysis, MALDI-TOF MS, antibody-drug-conjugate analysis and characterization

I acted as a teaching assistant, instructing undergraduates in proper laboratory techniques. I also worked as a graduate student researcher. My research focused on using computational techniques to determine desirable synthesis candidates, using combinatorial chemistry to synthesize those, and determining attributes that contribute to increasing bioavailability. I also served as the laboratory safety officer, developing SOP's and enforcing safety regulations.