AI Training Data Specialist

🔒 Confidential Employer
Posted 13 August 2025
LOCATION
United Kingdom
TYPE
Full-time
LEVEL
Entry-level
CATEGORY
Technology
This employer holds a UK Home Office sponsor license — sponsorship for this specific role is at the employer’s discretion

SKILLS

Data Annotation Data Management Data Quality Assurance Labeling Tools Data Pipelines Communication Skills

FULL DESCRIPTION

Summary

The AI Training Data Specialist will collect, clean, and annotate data to support AI projects. They will manage datasets, ensure data accuracy, collaborate with data scientists, and use labeling tools for various data modalities. Quality assurance and strong communication are key.

Key Responsibilities/Duties:

  • Collecting, cleaning, and annotating data to support supervised and unsupervised learning tasks
  • Managing and maintaining large datasets for model training, testing, and validation
  • Ensuring data accuracy, consistency, and relevance across various AI applications
  • Collaborating with data scientists and ML engineers to define labeling requirements
  • Using labeling tools and platforms to annotate data across text, image, audio, or video modalities
  • Conducting quality assurance checks and feedback loops to continuously improve dataset quality

Core Requirements/Qualifications/Skills:

  • Experience working with training data pipelines or annotation platforms (e.g., Labelbox, Prodigy, Scale AI)
  • High attention to detail and understanding of the role data plays in model accuracy
  • Familiarity with data formats (CSV, JSON, XML) and data management practices
  • Strong communication skills and ability to interpret labeling guidelines
  • Background in computer science, linguistics, AI, or a related field is a plus
  • Ability to work independently and collaboratively with technical teams

What You’ll Be Working On:

  • Collecting, cleaning, and annotating data to support supervised and unsupervised learning tasks
  • Managing and maintaining large datasets for model training, testing, and validation
  • Ensuring data accuracy, consistency, and relevance across various AI applications
  • Collaborating with data scientists and ML engineers to define labeling requirements
  • Using labeling tools and platforms to annotate data across text, image, audio, or video modalities
  • Conducting quality assurance checks and feedback loops to continuously improve dataset quality

What We’re Looking For:

  • Experience working with training data pipelines or annotation platforms (e.g., Labelbox, Prodigy, Scale AI)
  • High attention to detail and understanding of the role data plays in model accuracy
  • Familiarity with data formats (CSV, JSON, XML) and data management practices
  • Strong communication skills and ability to interpret labeling guidelines
  • Background in computer science, linguistics, AI, or a related field is a plus
  • Ability to work independently and collaboratively with technical teams
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