Google
Senior Research Data Scientist
- •Architected and built a Python library for LLM-based quality evaluation framwork, enabling parallel execution of prompt DAGs and automated quality evaluation metrics
- •Researched novel techniques in meta prompts and agentic workflows; built testing and validation suite to evaluate AI rater quality at scale and measure outcome variability
- •Created metrics to improve Google Discover recommender system, validating retrieval algorithm quality and performance
- •Provided technical guidance on experiment design and analysis, identifying meaningful lift across key user sub-cohorts
Apple
Senior Machine Learning Engineer / Data Scientist
- •Led cross-functional teams in developing, shipping and maintaining core on-device ML algorithms to users:
- •Meal logging tool with food image classification and LLM nutrition feedback
- •Personalized workout recommender system using a multi objective loss function and online learning
- •Unsupervised walk detection algorithm from steps data
- •Contextual notifications engine using routine identification (commute to work, typical workout time, etc)
- •Evaluated performance of ML models with focus on safety, robustness and privacy and efficacy communicated tradeoffs to partners
- •Architected data schema and privacy preserving data collection framework for launch of multiple health related programs and research studies (Lumihealth, Heartline, Attain)
- •Created application for labeling health data to create datasets and provide human feedback for models
- •Built data pipelines to process high volumes of medical claims data and health sensor data
- •Designed research studies and experiments to study impact of digital interventions and models on hypertension, diabetes, asthma, MCI and atrial fibrillation
