Reducto @ MIT
Join us for a technical deep dive with researchers (and fellow MIT alum) from Reducto, a hyper-growth AI startup specializing in document intelligence and data extraction at scale.
Reducto's ML research team will share their work on building state-of-the-art AI systems, working at a hyper-growth startup, and much more!
Date: Wednesday, Feburary 18
Time: 6:00 PM - 7 PM EST
Location: Stata Center, Room 32-141
Hosted by: AI@MIT + Reducto
Expect to hear about:
The technical architecture behind modern document understanding systems
Novel approaches to handling complex document layouts and hierarchical structures
Complex chart/graph understanding
RL for document tasks
Steerable + promptable layout detection
Document editing with AI
Real-world challenges in production ML systems for document processing
What it's like working at a Series B startup in SF!
Speakers:
Evan Volgelbaum (C'23) - Evan is an ML engineer at Reducto, previously at Hudson River Trading working on quantitative research in algorithm development.
Ray Wynne (C'21) - Ray is an ML engineer at Reducto and pursuing his PhD in Particle Physics at Caltech. He previously also did research at many MIT labs (MIT IAIFI, Kavli Institute, Center for Theoretical Physics).
Who should attend:
This talk is ideal for graduate students, researchers, and anyone interested in document AI, computer vision, NLP, or applied ML systems. Also for anyone who is curious about what it's like working at an AI infra startup!
We're also hiring across many roles: https://reducto.ai/careers
Please RSVP on this Luma page, as spots are limited!