Member of Technical Staff

Sieve · San Francisco, California · Posted 2025-09-02

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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 a software engineer at Sieve, you'll work across the stack to build and scale the data pipelines that create the datasets we deliver to customers. You'll have ownership over projects end-to-end: from how data is sourced and curated, to developing ML filters, improving system efficiency, and building internal dashboards for QA and delivery. You'll play a critical role in ensuring customers receive high-quality data on time, every time.

This role is ideal for someone who thrives on solving hard problems, enjoys working directly with customers pushing the frontier of multimodal AI, and wants to be challenged to achieve at the highest level.

Requirements ------------

Benefits ------------

*all roles at Sieve require you to be onsite in San Francisco 5 days per week

About Sieve

Sieve is an ML infrastructure company that provides easy to use APIs, infrastructure, and interfaces for video AI.

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Updated 2026-10-10.