Experience
Apr 2026 -
Present
AI Product Operations & User Research ,
Apple, Cupertino, CA
• Conducted product discovery and user research through 50+ Wizard-of-Oz studies, usability tests and Voice-of-Customer interviews, identifying user needs and feature opportunities.
• Drove ML Ops workflow improvements by identifying QA and data annotation pain points, defining, LLM-assisted review capabilities, improving the AI data pipeline, and reducing projected review effort by 30%.
• Enhanced the product roadmap by proposing an AI-powered feature for internal annotation tools, translating moderator pain points into feature requirements for future workflow improvements.
• Led cross-functional collaboration in an Agile environment across a team of 12, delivering multilingual AIML initiatives spanning 500K+ assets, 150+ batches, and 2 vendors while maintaining timelines and data quality.
Aug 2025 -
Mar 2026
AI Product Manager,
EchoLab, San Francisco, CA
link to the project
• Led 0-to-1 development of a GenAI-powered A/B hypothesis generation platform from concept to MVP in 4 months, reducing experiment setup time by 85% and increase experimentation capacity by 5×.
• Defined product requirements for an agentic AI workflow, including the RAG architecture, data pipeline, LLM prompting strategies, AI evaluation framework, and success metrics in partnership with AI engineers.
• Conducted Voice-of-Customer interviews with 10 early adopters, authored PRDs, identified experimentation workflow pain points, and evaluated market opportunities to shape product strategy.
• Defined the product roadmap by synthesizing customer feedback and market research to prioritize features.
Jun 2024 -
Aug 2024
Product Manager / MLE Intern,
211 LA, Los Angeles, CA
link to the project
• Led delivery of an MVP conversational AI referral assistant for Los Angeles County residents, reducing call handling time by 32% and increasing caller satisfaction by 11%.
• Designed a Retrieval-Augmented Generation (RAG) pipeline with human-in-the-loop review and AI guardrails, reducing hallucinations while improving recommendation relevance and regulatory compliance.
• Defined product requirements and success metrics by partnering with stakeholders to translate referral workflows into conversational AI capabilities, balancing automation, compliance, and user trust.
• Developed evaluation metrics and feedback loops to assess response quality and continuously improve conversational AI performance through prompt refinement and model fine-tuning.
Education
2023 - 2025
University of Southern California
MS in Computer Science - Applied Data Science
2019 - 2023
Shanghai Jiao Tong University
BS in Electrical and Computer Engineering
Minors: Data Science, Entrepreneurship
Honors: 1st class Outstanding Scholarship, Academic Progress Scholarship
Skills
& Expertise
Product Management & Business:
Product Strategy, Product Design, PRDs, Discovery & User Research, A/B
Testing, Experiment Design, Feature Prioritization, Agile, GTM, Cross-functional Leadership, Roadmapping, Stakeholder Communication, Product Storytelling, Jira/Linear/Notion
Technical:
RAG, Agentic AI workflow, LLM, Generative AI, Prompt Engineering, AI Evaluation, HITL, ML Ops, Prototyping, Machine Learning, Data Visualization, Data pipeline, Cloud (AWS/GCP), Databases, Python, SQL, Git