Member of Technical Staff, Infrastructure

About Us Sieve is a multi-modal lab curating the world's highest-quality training datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data. We partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people. We also raised our Series A from Tier 1 firms such as Matrix Partners , Swift Ventures , Y Combinator , and AI Grant . Why Now Sieve is one of the most capital-efficient teams in AI — roughly 30 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier. About the Role As an infrastructure engineer at Sieve , 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 + Fu