over 1 year ago
Base Salary
$150k - $300k/yr
Responsibilities
- Design and engineer systems for compute, scheduling, and orchestration of complex ML and ETL pipelines
- Optimize distributed systems for speed, reliability, uptime, and cost efficiency
- Build and operate systems at the scale of thousands of GPUs
- Develop internal tooling and CI/CD infrastructure to support rapid iteration
Requirements
- At least 3 years of experience building foundational data infrastructure
- Proficiency working across diverse cloud architectures
- Experience designing and maintaining pipelines that process petabytes of data
- Experience developing robust CI/CD pipelines for ML-focused teams
- Strong coding experience with Go and Python
- Rust experience is a plus
- Experience with large-scale video data systems
- Works as an individual contributor who leads by example
- Must work in person at the San Francisco headquarters
Benefits
- 401(k) and full health insurance
- Breakfast, lunch, dinner, and snacks covered
- Ubers home covered
- In-person work at the San Francisco headquarters
About Sieve
Sieve builds datasets and infrastructure for training video AI models, combining large-scale video processing with novel video understanding techniques. Its tools support ML teams working on media, gaming, AR/VR, and robotics by supplying high-quality video training data and pipelines. Founded in 2016 and headquartered in Palo Alto, the company operates as a privately held AI lab focused exclusively on video data.