Job Description & How to Apply Below
Key Responsibilities Accurately generate, annotate, and label diverse datasets following detailed, project-specific guidelines.
Review and validate annotations to ensure consistency, accuracy, and alignment with data ethics standards.
Collaborate closely with data scientists and machine learning engineers to meet specific dataset requirements.
Utilize annotation tools (e.g., Labelbox, Prodigy, etc.) and contribute to refining annotation guidelines and quality control processes.
Identify, document, and report data quality issues, edge cases, and unclear scenarios to continuously improve datasets.
A Typical Day Data Annotation: Generate and annotate synthetic and real-world datasets tailored for specific AI and ML models.
Quality Assurance: Perform rigorous validation checks to maintain annotation consistency and accuracy.
Collaboration:
Coordinate regularly with the data science team to align on dataset requirements and improvements.
Problem-Solving: Address annotation challenges and propose practical solutions for data enhancement.
Required
Skills & Qualifications Strong attention to detail with exceptional accuracy in annotation tasks.
Effective communication skills with the ability to clearly articulate decisions and feedback.
Proficient in English, both written and verbal.
Preferred Qualifications Demonstrable experience in data annotation, labeling, or similar roles.
Familiarity with data annotation tools and platforms.
Bachelor’s degree in Linguistics, Business Administration, Computer Science, or related fields.
Familiarity with AI, ML, and data science concepts.
Experience with scripting languages such as Python for automated data processing.
Understanding of data privacy laws and ethical considerations in data generation.
Previous work with diverse datasets (text, images, audio).
What You'll Gain Flexibility and autonomy in a fully remote, full-time position.
Opportunity to significantly contribute to state-of-the-art AI/ML developments.
Professional collaboration with global data science and AI teams.
Competitive compensation based on experience and skills assessment.
Potential performance-based incentives.
Application Process
To apply , please submit your resume clearly detailing your experience with data annotation and relevant qualifications.
Candidates may be asked to complete an online assessment evaluating:
Annotation accuracy and attention to detail
Understanding of annotation guidelines
Ability to effectively use annotation tools and software
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