Biography

I’m an AI/ML PM at Google, working to protect the Google Ads ecosystem from ad fraud and bad actors. Right now, I’m a PM rotator in Ad Traffic Quality. My work in Ads Safety focused on driving efforts to protect users and publishers from harmful content through better classification. Before that I worked on voice assistant research and development, including Siri and Alexa.

For 4 years as an AI/ML data ops and technical program lead at Google, I drove the execution of AI/ML programs for ads safety and policy, bridging the gap between product strategy, data science and engineering. I’ve led large-scale, multi-year operational migrations across organizations, pioneered new LLM and human data labeling strategies, and delivered significant business improvements (e.g. +$119M ARR model launch, -20% annual opex savings). I have extensive experience driving ML initiatives end-to-end from conception to launch.

I’m excited about emerging tech in the AI/ML space, and applying deep technical expertise to build useful products, particularly in the areas of digital ads and human language technology. I graduated from Stanford with a PhD in Linguistics (2018), and authored the book Optimal Linking Grammar (Cambridge University Press, 2023).

Areas of expertise:

Product & program leadership:

• Product strategy & vision for AI/ML systems
• Technical program management & cross-functional execution
• Stakeholder management & communications
• Roadmap development & planning

AI/ML expertise:

• LLM strategy (data generation, labeling and evaluation)
• NLP (ASR, TTS, NLU) and Human Language Technology
• Machine Learning & Deep Learning (classification models, prototyping)

Data science & analytics:

• Experimental design, A/B testing
• Evaluation metrics, KPIs, hypothesis testing
• Statistical analysis, data modeling

Technical proficiencies:

• Python, R, SQL (for data analysis & research)
• Git, Unix