AI Home Architecture Startup Looking for Back End/ML Infra Engineer
TL;DR
I run a YC company called Drafted.ai that allows people to design a house with the help of our AI. We've had 120k+ people come to the site and 20k+ signups since launching 3 months ago. We’ve raised $17M since starting the company 8 months ago, from Buckley Ventures (Josh Buckley), YC, Convective (Bill Clerico), Patrick Collison, Ben Silbermann, Jack Altman, Starship Ventures, Moses Moody, Ryan Tedder, Kevin Mahaffey, Charlie Songhurst. We are looking for a killer infrastructure/backend engineer who can help with the core product infra and model training infra. We have a major gap to fill with someone who is fast-paced, detail-oriented, and hungry to grow. The experience we are looking for: 1. Experience building and scaling GPU-based inference services, optimizing for both low latency and high resource utilization. 2. Experience with job orchestration and load balancing with parallel ge.
Nauti's Take
Drafted. ai shows real product-market fit in AI-assisted architecture — 120k visitors and $17M raised in three months is hard to dismiss.
The open question is whether the model scales when real construction projects introduce regulatory and technical complexity beyond rendering. For anyone eyeing AI-native design careers, this is a company worth watching.
Summary
I run a YC company called Drafted. ai that allows people to design a house with the help of our AI.
We've had 120k+ people come to the site and 20k+ signups since launching 3 months ago. We’ve raised $17M since starting the company 8 months ago, from Buckley Ventures (Josh Buckley), YC, Convective (Bill Clerico), Patrick Collison, Ben Silbermann, Jack Altman, Starship Ventures, Moses Moody, Ryan Tedder, Kevin Mahaffey, Charlie Songhurst.
We are looking for a killer infrastructure/backend engineer who can help with the core product infra and model training infra. We have a major gap to fill with someone who is fast-paced, detail-oriented, and hungry to grow.
The experience we are looking for: 1. Experience building and scaling GPU-based inference services, optimizing for both low latency and high resource utilization. 2. Experience with job orchestration and load balancing with parallel ge
Sources