About the Role
This role involves generating, reviewing, and refining data used to train AI and machine learning models, ensuring accuracy, relevance, and consistency across diverse datasets.
Responsibilities
- Create and annotate datasets to support machine learning development
- Evaluate AI-generated outputs for factual accuracy and coherence
- Follow guidelines to maintain data consistency and quality standards
- Identify and flag ambiguous or problematic content in training data
- Provide feedback to improve data labeling frameworks
- Work with structured and unstructured data formats
- Meet quality and throughput benchmarks on assigned tasks
- Adapt to evolving project requirements and instructions
- Collaborate with team leads to resolve data-related questions
- Maintain confidentiality of sensitive project information
- Contribute to the development of training examples for NLP models
- Assess text for logical flow and contextual appropriateness
- Classify data according to predefined taxonomies
- Ensure compliance with ethical data use policies
- Report technical or procedural issues promptly
- Participate in calibration sessions with team members
- Review multilingual content where applicable
- Follow version control practices for updated guidelines
- Support quality assurance checks on peer submissions
- Engage in periodic training refreshers
- Handle edge cases in data with clear documentation
- Contribute to test sets for model validation
- Use annotation tools efficiently and accurately
- Maintain consistent communication within the team
- Stay updated on project-specific objectives and changes
Nice to Have
- Prior work in data annotation or model training support
- Experience with natural language processing tasks
- Background in cognitive science or computational linguistics
- Exposure to AI ethics or responsible AI principles
- Multilingual abilities in additional languages
Compensation
Competitive hourly rate based on experience
Work Arrangement
Remote position with flexible scheduling options
Team
Collaborative team environment focused on AI training and data quality
Project Focus
Work will center on improving AI model responses through targeted data input, focusing on clarity, safety, and contextual accuracy.
Work Schedule
Tasks can be completed asynchronously within defined deadlines, allowing contributors to choose their active hours.
Not available for this role
