Seattle, Washington, United States
LLM-Powered Routines
* Designed and implemented an LLM-driven service to create Alexa Routines, focusing on scalable, configuration-driven code which can handle hundreds of API formats.
* Partnered with science teams to generate supervised fine tuning (SFT) and in-context learning (ICL) training data, evaluate model output, and overcome LLM limitations such as hallucinations and non-determinism. Altogether, increased model accuracy from 58% to 94%, unblocking project launch.
Routine Recommendation Builder
* Redesigned data stores and APIs used to suggest Routines to customers, accelerating recommendation creation, simplifying data contracts, and facilitating personalized recommendations and embedded upsells within Routines.
* Led a team of 5 developers to build an internal website tool for no-code creation of Routine recommendations. Website reduced the creation timeline from 4 weeks to 1 week and enabled project managers to quickly build dozens of recommendations, driving adoption by millions of customers and achieving our yearly engagement goals.
Leadership and Operational
* Managed 2 full-time employees and 1 intern for 6 months and mentored multiple other entry-level engineers and interns.
* Responded to customer-impacting experience-breaking events and addressed service operation issues as part of a cross-team on call rotation.