About HumanSignal 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. AI Data Collector — Turn the World Into Your Workplace! About the Opportunity We’re building a global community of detail-oriented contributors who help improve the quality of datasets used to develop advanced technologies such as artificial intelligence and computer vision systems.

As a Data Annotation Contributor, you’ll help review and refine labeled data to ensure accuracy and consistency. We are preparing for several upcoming initiatives and are inviting qualified contributors to join our growing community. By joining our contributor network, you’ll be among the first to hear about annotation projects that match your skills and location.

What You’Ll Do

Depending on the project, contributors may be asked to review and correct labeled data within images or videos. Tasks may include: Reviewing and correcting bounding boxes around objects or people Adjusting or refining segmentation or masking areas within images Identifying and masking personally identifiable information (PII) when required Ensuring annotations follow detailed project guidelines and quality standards Flagging unclear or incorrect labels for review Submitting completed annotation tasks through designated tools or platforms Each project will include clear instructions, examples, and support from our team. How Our Community Works Once you join our contributor community, you will: Receive notifications about upcoming or ongoing data annotation projects Review project details and decide whether you’d like to participate Complete annotation tasks that match your skills and availability Gain access to future opportunities as new projects are launched Participation is flexible, allowing contributors to select the projects they want to work on.

What We’Re Looking For

We’re looking for contributors who are: Highly detail-oriented and focused on accuracy Comfortable following structured guidelines and quality standards Able to work independently and manage tasks responsibly Strong communicators when questions or clarifications arise Comfortable using online tools for reviewing or editing data Previous experience with data annotation, image labeling, or quality review is helpful but not required. Training materials may be provided depending on the project.

Compensation

will vary depending on the specific project and the country or region where the work is performed. Pay rates will be communicated prior to the start of each project and are designed to align with competitive rates for similar work in your location. Why Join Our Contributor Community Flexible opportunities to participate in data annotation projects The ability to contribute to the development of emerging technologies Access to a growing pipeline of global annotation initiatives Clear instructions and support from experienced project teams If you enjoy detail-oriented work and want to contribute to improving real-world datasets used in advanced technologies, we encourage you to apply and become part of our annotation contributor community.