Real-world data is the competitive edge in AI.
HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery.
We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide.
We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out.
If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk.
Moderators run our in-person data collection sessions. You'll set up the recording equipment, walk participants through their tasks, keep the session on track, and make sure the data we capture is clean and usable. It's part technical, part people. The best moderators are the ones who can troubleshoot a camera rig and put a nervous first-time participant at ease in the same five minutes.
You'll work with interesting capture technology, build real facilitation experience, and see exactly how the data behind modern AI gets created. Flexible part-time scheduling around active projects.
HumanSignal is an equal opportunity employer. Final pay within the posted range is based on experience and equipment scope.
HumanSignal enables data science teams to build AI models with their company DNA. With the emergence of generative AI, it’s more important than ever to build highly differentiated models by guiding foundation models with proprietary data and human feedback. Creators of Label Studio, the most popular open source data labeling platform, HumanSignal enables data scientists to develop high quality datasets and workflows for model training, fine tuning and continuous validation.
Today, the Label Studio open source community has more than 250,000 users who have collectively annotated more than 100 million pieces of data. Label Studio Enterprise is available as a cloud service with enhanced security, automation, quality review workflows, and performance reporting, used by leading data science teams including Bombora, Geberit, Outreach, Wyze, and Zendesk.
