Product Engineer at Sieve (W22)
Video AI for Developers
San Francisco, CA, US
Full-time
1+ years
About Sieve

Sieve is a specialized cloud built for video / audio AI.

Every video product today is being overwhelmed by a ton of new use cases that are enabled by AI. Video is unique in that it’s much more compute and data-intensive to process or generate compared to other modalities. This leads to a ton of complexity around the ways models are run, the kinds of extra processing needed to happen around them, and the complexity of pipelines that solve the most valuable use cases in the modality. To this end, Sieve’s strongest and most immediate value proposition comes from being an AI toolkit that solves problems unique to video — unlike generic AI developer tools that might exist today.

Video is just the start however. Learn more about our long term vision here!

About the role

Sieve’s product involves a frontend website + dashboard, a Python client, a CLI, and an API (https://docs.sievedata.com). You’ll spend most of your time building improving these things and probably have a great knack for what a delightful developer experience feels like.

Our current stack for these things involve Next.js, Python, Go, and Kubernetes though you don’t need to be familiar with all of it to start.

  • Great attention to detail and obsessing over the little things
  • Prior experience shipping full stack products
  • Great communication skills
  • Interest in machine learning

Check out this page to learn more about the company and what it's like to work with us!

https://sievedata.com/about/jobs

Technology

As an early engineer, you’ll get to:

  • work on low level containerization, networking, and distributed systems problems impacting thousands of GPU workloads at any given moment
  • write and deploy code that touches users every single day
  • work with the latest generative models
  • make decisions on product experience and design
  • interact directly with customers in calls, shared Slack channels, etc.

We primarily code in Go, Python, and Rust. Additionally, we heavily utilize Redis, Prometheus, Loki, Grafana, MongoDB, Pulumi, and Clickhouse. Our frontend is build with Next.js.

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