Tiffany started as an executive assistant at a family-run manufacturing company before taking a break. After being discovered on LinkedIn by Chris, she took a trial PM role in an audio data collection project—where she had to source all the participants herself. That hands-on, build-it-yourself start became the foundation of her career at Sapien.
With only a script and a budget, Tiffany launched a data collection campaign targeting Taiwanese-accented speakers. She coordinated outreach across job boards, college platforms, and social media, proving herself under pressure and earning a full-time offer shortly after.
While AI models have made massive strides, math remains a weak point. Jiaxiao’s work focuses on training models to reason through high school-level problems using step-by-step chain-of-thought methods—critical for making models more reliable.
In a standout moment, Tiffany described visiting a Sapien labeling center in Beijing, seeing rows of students labeling data for autonomous driving models. The experience reinforced her belief in the social and technical impact of Sapien’s work.
She’s vocal about improving quality of life for data workers: “I couldn’t do eight hours of labeling either, so we’re constantly thinking about how to make the job more comfortable, whether it’s physical support, better breaks, or thoughtful workflows.”
Tiffany sees AI as a vast career frontier and Sapien as a launchpad: “We’re giving people not just tasks, but career stepping stones in one of the most important industries of the future.”