New Grad AI Data Quality Specialist

Hire Feed; España; On-site; EUR 24,000 - 32,000; Full time

Job summary

Hire Feed is seeking a Human Data Manager, New Grad to join a global technology leader focused on AI data quality and high-quality datasets used in model training and evaluation. You will ensure accuracy and consistency across labeling tasks and help refine data pipelines.

This entry-level position offers hands-on exposure to data annotation guidelines, quality checks, and collaboration with cross-functional teams to improve data quality for machine learning applications.

Qualifications

• Experience with data annotation, labeling, or quality assurance processes is preferred.
• Familiarity with basic data validation techniques and attention to detail in reviewing datasets.
• Ability to follow structured guidelines and maintain consistency in data handling tasks.
• Basic understanding of AI/ML concepts and their dependence on high-quality training data is beneficial.
• Proficiency in using spreadsheets or data management tools to track and organize information.

Responsibilities

• Review and validate human-labeled data to ensure consistency and accuracy for AI training datasets
• Identify and resolve discrepancies in data annotations by cross-referencing source materials and guidelines
• Collaborate with cross-functional teams to refine annotation guidelines and improve data quality standards
• Monitor and report on data labeling performance metrics to track progress and identify trends
• Assist in documenting processes and maintaining records of data sources, labeling rules, and quality checks

Skills

data annotation

quality assurance

data validation

attention to detail

data management tools

Job description

Hire Feed is seeking a Human Data Manager, New Grad to join a global technology leader focused on AI data quality and high-quality datasets used in model training and evaluation. You will ensure accuracy and consistency across labeling tasks and help refine data pipelines.

This entry-level position offers hands-on exposure to data annotation guidelines, quality checks, and collaboration with cross-functional teams to improve data quality for machine learning applications.