Apr 2023 – Present · 3 yrs · Remote

Mar 2023 – Present · 3 yrs 1 mo · Remote

Jan 2022 – May 2023 · 1 yr 4 mos

May 2020 – Nov 2020 · 6 mos · United States

• Research intern at Google Brain.
• Contributed key mathematical and algorithmic insights into a new self-supervised pretraining method that leverages recent advances in differentiable sorting for representation learning
• Defined new state of the art performance for audio and vision based tasks
• Streamlined and standardized several scattered experiments across notebooks and code bases. This drastically increased team productivity and we were able to launch multiple large scale experiments daily
• Designed and developed two novel metrics to measure experimental success now used by the team to communicate our findings
• Orchestrated foundational experiments across thousands of GPUs and decreased data loading time from 5 minutes to 300ms
• Explored mathematical relationship between entanglement and optimal transport distance, presented work to team
• Reproduced results from the field which increased our ability to iterate and improve upon existing research

Jan 2020 – Jan 2021 · 1 yr

• Fellow on the code generation team working on Codex which powers GitHub Co-Pilot.
• Scaling laws for data quality with improvements resulting in a 2x performance boost on HumanEval

Jun 2019 – Aug 2019 · 2 mos · Palo Alto, CA

• Prediction intern on the Level 5 Self-Driving team.
• I worked on dynamical vehicle prediction using physics, machine learning, and data driven models. I improved the performance of the system 22.5%
• I wrote high performance, modern, c++ for this project for real time feature extraction and trained models using Python. These models were deployed to the car with Tensorflow.
• I also worked on an internal semantic code search tool using modern transformers, NLP, and Pytorch

May 2018 – Aug 2018 · 3 mos · Provo

• ML Engineering intern on NLP / Text understanding team.
• Researched and implemented phishing detection tool using sophisticated feature engineering, random forest, and logistic regression techniques. Achieved ∼96% accuracy with a .005% false positive rate
• Engineered and developed asynchronous API using parallel processing and high performance computing techniques to achieve a 3x speed up resulting in a 63% reduction in hardware costs
• The final estimated impact of this project is $300k - 500k in savings.
• Built question similarity tool using sentence embeddings after collecting and curating a dataset of ∼130,000 questions. Improved f1 score from .3 to ∼.7
• Read, implemented, and improved methods for emerging topic tracking from state of the art papers. Resulting in a functioning prototype that allowed my team to reach their stretch goals for the quarter

Jul 2017 – Apr 2018 · 9 mos · Provo

• Designed and taught a competitive coding course to talented math majors with topics focusing on algorithm design, problem solving, data structures, and mathematical familiarity for solving programming questions.
• Of my students, 12 placed in the top 20 at the Fall 2017 ACM coding competition.
• Our team placed in the top 50 in the annual hackerrank collegiate challenge

Dec 2016 – Apr 2018 · 1 yr 4 mos · CS

• Member of Amazon Alexa Prize Team Eve
• Designed and built an offensive speech filtering system using probabilistic methods, which performed ~3% better than current industry standards
• Researched and designed a complex sentiment analysis tool that didn't only classify sentences as positive, negative, or neutral but also determined if the sentiment was complex.
• Research Assistant
• Collaborated on machine learning project researching low cost MRI configurations
• Developed machine learning models to improve relatively poor quality imaging allowing
• for wide spread medical imaging
• Developed parallel solutions to augment arbitrary image data sets, and simulate MRI results reducing processing time by 300%
• Designed and built a deep learning platform to reduce background noise for hearing aid users resulting in a system that reduced the signal to noise ratio by 197%
• Identified and assisted with various bug fixes to learning algorithms and probabilistic programming models
• Assisted in formulating convergence proofs for DFA like Deep Learning learning systems
• Most of the work done involved Pytorch. We did all of our work on Linux systems with Docker and Cuda.

May 2016 – Oct 2016 · 5 mos · Alpine, Utah

• Developed super powered web solutions to significantly increase employee effectiveness, resulting in significant annual savings
• Collected, cleaned, and analyzed internal and external data to pinpoint areas of business strength and weakness
• Optimized daily processes, and increased page load speed by 75% (Python, MySQL)

Feb 2016 – Apr 2016 · 2 mos · American Fork, Utah

• Combined technical knowledge with business acumen to ensure apps were useful to consumers and accurate in their functions
• Personally created 160 Domo business apps that use data to tell the customer’s story (JS)
• Wrote killer documentation for customers

Sep 2015 – Apr 2016 · 7 mos · Provo, Utah, United States

• Discovered proper boundary condition equations to more accurately model pressure
• waves using numerical methods, resulting in a method of approximation that was 3x
• faster than previous methods
• Collected data on models, and tested our results for stability and consistency
• Presented research findings to experts, professors and fellow students

Jun 2015 – Aug 2015 · 2 mos · Pittsburgh, PA

• Developed custom web games and did user testing to help refugees learn English
• Excelled in Data Science course work earning top marks (Python)
• Presented secondary research to peers and mentors

Feb 2014 – Mar 2015 · 1 yr 1 mo · Provo, UT

• As a member of the BYU studies web team, I assisted in the maintenance of our ASP.NET systems, integration of new functionality, maintenance of our mySQL server, extensive front end design, and related administrative requirements.
• Led a web team of 3 in maintaining a website with thousands of unique visitors,
• increasing traffic and profitability by over 38%
• Managed a relational database, customer information, and new projects

Jun 2011 – Oct 2011 · 4 mos · Yakima, Washington

• Worked independently to develop firm's website, and sites for local companies.
• Assisted on the creation of electrical plans for University of Washington