Trace Wynecoop - Homepage

Experience

Designing bots to gather data from across the internet in support of generative AI initiatives at Amazon

Assisted in delivering a $100 million feature for the Alexa+ and Nova AI launches by parsing websites for targeted information
Improved customer relations by designing tools to give content owners more control over how their data is used

Built and maintained internal testing services for AI and Large Language Model development

Designed and implemented a tool using Python to fine-tune Large Language Models (LLMs), which improved model accuracy and performance for Alexa
Built an internal AI testing website using TypeScript that enabled tens of thousands of Machine Learning scientists to efficiently validate their models

Created data insights that have a visible impact across Alexa’s AI systems, including personalized experiences on the front page of Alexa devices

Developed a data service using Python and AWS that delivered personalized information to millions of Alexa users
Led a long-term project aimed at improving Alexa’s Speech Recognition by increasing knowledge of trending names and terms
Led the development on a long-term project which aimed to improve Alexa’s Speech Recognition by increasing knowledge of trending names and words

Worked alongside university faculty to create a digital keyboard with predictive and auto-correction capabilities, similar to those found on iPhone and Android. Utilized Java to organize and parse a database with half a million of the most popular English words scraped from around the internet.

Collaborated with a team of students to predict when a solar flare is likely to occur through the use of machine learning and data mining. Cleaned, pre-processed, and transformed data gathered from the web to create analysis reports. Used Python to train multiple machine learning models on the final data sets.

Overhauled Eastern Washington University’s grading tools for the Computer Science department by using Java and PHP to deploy an AWS server that automatically grades each student’s programming homework. This system has vastly reduced the workload for TA’s by allowing them to simply upload a zip file containing each student’s submission, with the program displaying their final score. It is currently being used to administer the Advancement Programming Exam to all of their CS Students.

Bachelor of Computer Science, 3.96 GPA

Graduated Summa Cum Laude.
Built a strong foundation in Computer Science and Mathematics. Worked on research projects with faculty, contributing to the development of tools for the university like automatic grading systems. Consistently recognized on the Dean's List for academic excellence and commitment to high-quality work.