AI/LLM Data Trainer & Quality Annotator

CSEA; Philippines; Remote; PHP 83,000 - 165,000; Full time

Job summary

CSEA in the Philippines is seeking a data annotation specialist to create training data sets for AI models, ensuring high accuracy and linguistic quality. You will annotate data to align outputs with human values and collaborate with data scientists and engineers to refine data recipes.

The role requires adapting to changing guidelines while meeting daily KPIs for data production and efficiency. This position focuses on improving model performance through precise linguistic work.

Qualifications

• Experience creating training data sets for AI models
• Ability to annotate data with high accuracy and consistency
• Familiarity with linguistic conventions and data quality standards
• Comfort collaborating with data scientists, researchers, and engineers
• Ability to document processes and guidelines clearly

Responsibilities

• Create training data sets for AI models to improve accuracy, fluency, and coherence
• Annotate data to align AI outputs with human values and guidelines
• Analyze grammar, syntax, and sentence structure to ensure linguistic quality
• Collaborate with data scientists, researchers, and software engineers to refine data sets
• Contribute to evolving specifications for AI model training and data recipes
• Adapt to shifting guidelines and flexible priorities
• Meet KPIs such as daily data production targets and average handling time

Skills

Data annotation

AI training data

Quality assurance

Cross-functional collaboration

Process documentation

Job description

CSEA in the Philippines is seeking a data annotation specialist to create training data sets for AI models, ensuring high accuracy and linguistic quality. You will annotate data to align outputs with human values and collaborate with data scientists and engineers to refine data recipes.

The role requires adapting to changing guidelines while meeting daily KPIs for data production and efficiency. This position focuses on improving model performance through precise linguistic work.