Applied Scientist II, Core Shopping Data Science
Core
Design and build LLM-based measurement pipelines to quantify ambiguous customer perception defects in the shopping experience (search, homepage, detail pages) and establish production standards for quality evaluation.
Role type
Applied Scientist II (LLM-based measurement & evaluation)
Builds
Reusable labeling pipelines, evaluation frameworks, inference infrastructure, and golden datasets for customer experience measurement.
Domain
E-commerce / Customer Experience / Large-scale ML
Deliverable
production ML models | product features
Required skills
LLM prompt design, sampling strategy, model validation against ground truth, distributed computing, high-performance computing, algorithm design, data mining, Java/C++/Python programming
Preferred skills
Unix/Linux usage, professional software development experience
Technologies
LLMs, Java, C++, Python, distributed computing frameworks
Responsibilities
Design LLM-based labeling for perception-driven defects; validate labeling quality and maintain golden datasets; extend measurement methodology to new shopping areas; build production-grade tooling for batch inference and version control; define standards for LLM usage in quality measurement; partner with cross-functional teams to integrate metrics into decisions.
Seniority
Senior, hands-on IC
