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.

Engineers on the team

• Work with Python, Django, Kubernetes, React, Redis, and Postgres
• Spend time directly interacting with customers to understand their problems
• Share frequent and honest feedback with each other
• Fork open source libraries to solve challenges unique to our business
• Help guide product decisions and high-level strategy

Skills & Experience

• 3+ years of experience building and maintaining infrastructure at scale
• Fluent with Docker/Kubernetes, EKS, KNative, Terraform, Terragrunt, Gunicorn, and Python
• Excellent writing and communication skills - can distill complex topics into bullet points
• Enthusiasm for AI / ML and open source software

Benefits

• Competitive salary and meaningful equity
• Flexible work environment – work remotely, or from our HQ in Cambridge, MA
• Health, dental, and vision benefits with 90% coverage for you and 50% for dependents
• Weekly all-hands meetings each Friday
• Quarterly in-person trips