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 the data and environments frontier AI labs use to train the next generation of multimodal systems. AI is moving beyond chatbots into video, audio, images, software, robotics, and interactive worlds. The next generation of models will need to understand how the world looks, sounds, moves, responds, and changes over time. Progress is bottlenecked by one thing: high-quality data. Sieve brings together exabyte-scale infrastructure, novel multimodal understanding techniques, large-scale sourcing, and deep research partnerships to create datasets and environments with unmatched precision, quality, and speed. This has earned the trust of frontier AI labs, Fortune 100 companies, and fast-growing AI startups working on generative media, robotics, computer use, world models, and agentic systems.