AI Infrastructure for Video
Sieve is hiring a founding designer.
Think about Sieve as something similar to Databricks or what Tesla's ML data engine looks like internally, but focused on video and built for software engineers and data scientists who may not know the ins and outs of deep learning and infrastructure.
We’re not building tools for ML engineers, we’re building tools for software engineers — which is why it’s evermore important that the product design is one that can be understood by folks that know very little, but also one that let’s ML experts tinker and take advantage of their expertise. Building this right means building great docs, a great dashboard, and a seamless onboarding experience whether it be in “one-click deploying” open-source repositories or starting from scratch. We think the dynamic of our product is very similar to what Vercel has built around Next.js and starter kits for specific use cases.
We’re looking for folks that are interested in AI / ML, will always have the developer in mind, and prioritize simple design with an attention to detail. You'd be in-charge of every part of the product experience and Sieve's online and offline presence from user onboarding flows, to open-source repository branding, our website and dashboard, and even our office art (lol).
In the late 90’s, humanity started contributing to a central store of all human knowledge — the internet. The internet back then was made up mostly of text, and to that end search engines like Google indexed it all — literally putting all human knowledge at people’s fingertips.
20+ years later, we’re at a crossroads where richer data types are being used to store human knowledge. 80% of the internets IP traffic today is video. Apps like TikTok have exploded, smart cameras exist almost everywhere from homes, to farms, construction sites, offices, retail stores, and warehouses, and we’ve been ushered into a new age of collaborative, creative tools with experiences such as Figma.
Unlike twenty years ago, human knowledge exists in more places and forms than ever. And every developer and company trying to build a new magical experience is left setting up AI / ML infrastructure, wondering why they have to manage datasets, and figuring out how to process, structure, search, and deliver resulting data to an end application.
Sieve’s mission is to build the core infrastructure needed to process, understand, and search the rich data — so developers can ship magical experiences faster. And video is just the start.