ML Engineer @Science Platform.

• Build software systems to help clients run geolift experiments and measure the effectiveness of their marketing campaigns with casual inference.

• Build ML solutions to better optimize geolift experiment flow and predicts.

ML @ discovery

• Product Feeds ranking. Personalized recommendation for buyers to see more listings that they would bid on or purchase.

• Livestream Feeds ranking. Personalized category feeds.

ML Engineer @ Instagram

• Train and serve caffe2/pytorch ML models for Instagram Reels recommendation system. Training data generation, feature engineering, label engineering, training, value model tuning, recurring publish, GPU inference, A/B testing, monitoring and alerts.

Machine Learning Engineer in Rider Pricing Team, optimizing tradeoff between growth and profitability.

• Model, train and serve tensorflow Deep Neural Network demand model.

• Training data generation, feature engineering for demand model.

• Pricing experiments to measure rider elasticity

• Designed and developed tooltips framework that powers multiple apps including Driver and Rider and used by more than 10 product teams.

• Shipped Uber's first tipping product and Uber's first loyalty program. Both project were large cross-team and cross-org collaborations and had a lot of media coverage.

• Shipped Learning Hub, which was a brand new product for the rewrite of the driver app.