Jobs Companies HumanSignal Data Annotation Contributor

À propos de ce poste Data Annotation Contributor chez HumanSignal

HumanSignal · International

The future of AI — whether in training or evaluation, classical ML or agentic workflows — starts with high-quality data.

At HumanSignal, we’re building the platform that powers the creation, curation, and evaluation of that data. From fine-tuning foundation models to validating agent behaviors in production, our tools are used by leading AI teams to ensure models are grounded in real-world signal, not noise.

Our open-source product, Label Studio, has become the de facto standard for labeling and evaluating data across modalities — from text and images to time series and agents-in-environments. With over 250,000 users and hundreds of millions of labeled samples, it’s the most widely adopted OSS solution for teams working on building AI systems. 

Label Studio Enterprise builds on that traction with the security, collaboration, and scalability features needed to support mission-critical AI pipelines — powering everything from model training datasets to eval test sets to continuous feedback loops.We started before foundation models were mainstream, and we’re doubling down now that AI is eating the world. If you're excited to help leading AI teams build smarter, more accurate systems — 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
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.

(Must reside in one of these countries, India, Pakistan, Bangladesh, Sri Lanka, Nepal, Philippines, Vietnam, Indonesia, Thailand, Malaysia, Kenya, Nigeria, Ghana, Uganda, Tanzania, Rwanda, Egypt, Mexico, Colombia, Peru, Argentina, Brazil, Bolivia, Guatemala) 

This is an independent contractor engagement and does not constitute employment with HumanSignal. Contractors are responsible for their own tax obligations in their jurisdiction. 

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À propos de HumanSignal

We build software that helps people do what only they can do – give meaning.

Data fills our modern world. It flows prolifically inside organizations, customer interactions, product usage, environmental research, healthcare imaging, and beyond. What if we could use any of this historical data to predict the future? In most cases, we can now make predictions through Machine Learning & AI, but to do so in a meaningful and impactful way, historical data needs to be accurate, comprehensive, and without bias.

 

To make the best predictions, we believe teams with domain expertise should be responsible for annotating and curating data. It's called data labeling, and it’s a process of real people giving meaning to the information they see on the screen. HumanSignal was founded to take data labeling operations to the next level and help data scientists make better predictions.

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