Replit for ML
Slai is a tool to quickly build machine learning-powered applications. Our browser-based sandbox is the easiest way to build, deploy, and share machine learning models with zero setup. Here’s an example app on our platform.
Dozens of data teams are using Slai to power their machine learning models in production. And we have a thriving community of developers using our platform to build apps using state-of-the-art models, like Stable Diffusion and GPT-2.
We’re looking to bring someone on to help us with SRE / DevOps work. If you like working on distributed systems and machine learning at scale, we have the role for you. Our system is used for rapidly creating serverless runtimes to run our customers' ML training code and autoscaling their deployments according to traffic. You'll be responsible for helping to scale our infrastructure to support the growth of our customers. Since we host ML models for customers, we grow when they do -- and boy, are some of them growing fast.
Slai is building the developer-friendly machine learning platform. We’re a different type of ML platform that enables developers to build state-of-the-art machine learning apps into their products.
Machine learning is eating software, but it’s still difficult for developers to leverage ML in their products. Today, companies are spending months building their own ML platforms, or relying on outdated tools that were originally designed for academics. We have spent our careers building developer tools, and have experienced this problem first hand. The existing solutions for shipping ML models don’t work.
We believe that for ML to reach widespread adoption, the underlying tools need to be redesigned for developers. Slai is unique because the entire ML development process happens in the browser; we manage the runtime, datasets, source control, and underlying cloud infrastructure with a single tool.