Gautam Kedia

Hello! I’m GK. I love building ML systems, investing, & doom scrolling. If you’re building a machine learning product, I would love to hear from you!

Work

2023-Current: Applied ML, Stripe

In 2023, I started a new Applied ML team at Stripe to bring LLMs & foundational models to Stripe. We’ve shipped dozens of applications across the company including support and docs assistants. We’ve also pre-trained foundation models on 1 trillion+ tokens, and working on many more interesting use cases.

2020-2023: Fraud Intelligence, Stripe

I led the Fraud prevention ML & engineering teams at Stripe. We reduced losses by double digits YoY while improving onboaring experience for Stripe users. We built state-of-the-art ML and backend systems that scaled with Stripe. Here are some of the models & systems including a transformer model on sequences of API calls, unsupervised clustering model that finds novel fraud attacks, and anomaly detection system to detect risky behavior

2018-2020: Applied ML, Lyft

I started the Applied ML team at Lyft. We shipped state-of-the-art applications across the company e.g ride destination recommendations with a transformer based model, revenue-optimizing mode recommendations, a Thompson Sampling based adaptive experimentation system, optimized tolls prediction pricing model, and coaching program for drivers who drive with their phone in their hands.

2015-2018: Office AI, Microsoft

I led the Smart Reply & Office AI prototyping team. Here are some projects that the team delivered:

State-of-the-art reccurrent neural net for predicting replies to Skype messages & Outlook emails
- ~100M parameter model trained on ~1B emails and serving ~10B emails per day!
- Handled correctness and bias in models
Prototypes for meeting detection, task detection, and summarization of emails

2010-2014: Bing, Microsoft

I led the Location Personalization & Cortana Ranking team at Microsoft.

gk