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AI data annotators providing the foundation for intelligent systems  

Specialists who label, classify and structure data to train accurate and reliable AI models.  

AI data annotators creating the labelled data your models learn from

AI data annotators are the engine behind high-quality training datasets. They label images, text, audio and video with precise, consistent annotations that machine learning models use to learn patterns, understand language and make accurate predictions.

Their work requires meticulous attention to detail, a clear understanding of annotation guidelines and the ability to handle large volumes of data efficiently without compromising accuracy. The quality of their output has a direct impact on model performance.

Sourcewiser's offshore AI data annotators are experienced in working within structured annotation workflows and integrating with your data pipelines. They bring speed, consistency and quality to your labelling tasks, whether for computer vision, NLP or multimodal AI projects.

Our annotators are proficient in tools such as Labelbox, Scale AI, Label Studio, Roboflow, CVAT, AWS SageMaker Ground Truth and Appen, with experience spanning image segmentation, text classification, named entity recognition and more.


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See what our clients have to say about working with us.

How it works

STEP 1 Define your needs
We align with your IT and tech goals, roles and unique organisational challenges.
STEP 2 Get matched
We shortlist the top 1% of IT and tech candidates and match to your requirements, tools and culture.
STEP 3 Choose your delivery model
Remote, hybrid or office-based - we build around your preferred setup.
STEP 4 Scale with confidence
You stay in control with ongoing support, performance tracking and delivery optimisation.

Key responsibilities

Responsibilities aligned to your goals and operational needs.

  • Label, tag and classify images, text, audio and video datasets according to project guidelines
  • Perform bounding box annotation, semantic segmentation and polygon labelling for computer vision tasks
  • Conduct text annotation including NER, sentiment labelling, intent classification and coreference resolution
  • Maintain high accuracy rates and flag ambiguous or edge-case data for review
  • Follow quality control processes and contribute to annotation guideline refinement

Platform-ready talent,
vetted for the tools you use

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Levels of experience

Choose from three clearly defined experience levels to match your needs.

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    Junior

    (1 - 3 years experience)

    Label images and text to spec

    Follow annotation guidelines

    Maintain throughput and accuracy targets

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    Intermediate

    (3 - 5 years experience)

    Handle complex annotation tasks

    Review and QA peer annotations

    Contribute to guideline updates

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    Senior

    (5+ years experience)

    Lead annotation projects end-to-end
     
    Design QA frameworks
     
    Manage and train annotation teams
     

Meet your future team members

An example of the expertise our offshore talent brings.

Frequently asked questions

What types of annotation do your specialists handle?

Our annotators cover a wide range of annotation types including image labelling (bounding boxes, segmentation, keypoints), text annotation (NER, sentiment, intent, classification), audio transcription and multimodal labelling for video datasets.

How do you ensure annotation quality and consistency?

We apply rigorous quality control processes including inter-annotator agreement scoring, QA review layers and structured guideline documentation. Our senior annotators conduct regular audits to maintain accuracy at scale.

Can your annotators work within our existing labelling platform?

Yes. Our team is experienced across all major annotation platforms. If you use a custom internal tool, we adapt quickly - most annotators are up to speed within a few days of onboarding.

Can I scale annotation capacity for a large data project?

Absolutely. We support both ongoing annotation needs and high-volume, time-sensitive projects. Our flexible model allows you to scale team size up or down based on project requirements.

Other IT and tech roles you can outsource

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Curated hires, no seat-fillers

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AI-matched, human-approved

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Flexible models, always-on support

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Fast deployment, long-term retention