## About Us
Sieve is the only AI research lab exclusively focused on video data. We combine exabyte-scale video infrastructure, novel video understanding techniques, and dozens of data sources to develop datasets that push the frontier of video modeling. Video makes up 80% of internet traffic and has become the enabling digital medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in growth of these applications: high-quality training data.
We've partnered with top AI labs and did $XXM last quarter alone, as a team of just 15 people. We also raised our Series A last year from Tier 1 firms such as [Matrix Partners](https://matrix.vc/), [Swift Ventures](https://www.swift.vc/), [Y Combinator](https://www.ycombinator.com/), and [AI Grant](https://aigrant.com/).
## About the Role
As a distributed systems engineer at [Sieve](https://www.sievedata.com/), you’ll design and engineer systems that handle the compute, scheduling, and orchestration of complex ML + ETL pipelines that need to run quickly, reliably, and cost-effectively on large sums of video.
You’re likely a good fit if you love optimizing for system uptime, have worked with cloud technologies, optimizing hyper-fast distributed systems at the scale of thousands of GPUs, and building great internal tooling and CI/CD for rapid iteration.
## Requirements
- 3+ years of experience building foundational data infrastructure
- Proficient in working across diverse cloud architectures
- Designed and maintained pipelines that process petabytes of data
- Developed robust CI/CD pipelines tailored for ML-focused teams
- Strong coding experience with **Go** and **Python;** Experience with **Rust** is a plus
- Operates as an IC who leads by example
- Experience with large-scale video data systems
- In-person at our SF HQ
## **Benefits**
- 401k + Full Health Insurance
- Breakfast, Lunch, and Dinner covered and your choice of snacks
- Ubers covered home
Visa sponsorship is not available for this role.
