Put your expertise to work on frontier AI
Join Snorkel’s Expert Community for paid, remote, project-based opportunities aligned with your professional, technical, or academic expertise. Help develop and evaluate the data and environments behind advanced AI models and agents.
Find paid opportunities to help train and evaluate AI
Advanced AI systems need more than large volumes of generic data. They need input from people who understand the disciplines, tools, workflows, and real-world decisions these systems are expected to handle.
Snorkel’s Expert Community brings together professionals and academics across more than 1,000 domains to contribute to frontier AI projects. Depending on the project, contributors may help create specialized datasets, evaluate model outputs, design realistic tasks, test AI agents, identify failure modes, or develop the environments used to train and evaluate advanced systems.
When a project matches your expertise, Snorkel may invite you to participate. You decide which opportunities to accept and contribute on your own time.
What kinds of AI training work does Snorkel offer?
Projects vary based on customer and research needs, but expert contributions may include:
| BENCHMARK | MODEL A | MODEL B | MODEL C |
|---|---|---|---|
| Benchmark 1 | 00.0% | 00.0% | 00.0% |
| Benchmark 2 | 00.0% | 00.0% | 00.0% |
| Benchmark 3 | 00.0% | 00.0% | 00.0% |
1. Snorkel AI
KEY INSIGHT
One non-numeric idea worth spotlighting inline — the thing the reader should leave with, in one sentence.
Snorkel AI takes a fundamentally different approach. Describe the key differentiators and why it’s the recommended alternative.
2. Alternative Name
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How to choose
The right platform depends on your specific needs. Here’s a quick decision framework.
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Frequently asked questions
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Alex Ratner is the co-founder and CEO at Snorkel AI, and an affiliate assistant professor of computer science at the University of Washington. Prior to Snorkel AI and UW, he completed his Ph.D. in computer science advised by Christopher Ré at Stanford, where he started and led the Snorkel open source project. His research focused on data-centric AI, applying data management and statistical learning techniques to AI data development and curation.
Scaling out Snorkel AI across EMEA and the international markets, heading up the ML Field Engineering and Solutions team.
Snorkel AI proposes a highly differentiated data-centric AI platform, helping unlock the value of your unstructured data for your GenAI and ML projects.