AI Data Specialist - Remote
About the Role
We are looking for an AI Data Specialist - Remote to support the improvement of AI-generated content in English. This role offers a flexible part-time schedule, allowing you to work from home in North Carolina. As an AI Data Specialist, you will be responsible for data collection, evaluation, and annotation, contributing to the enhancement of AI systems.
What You'll Do
- Collect and evaluate data to improve AI-generated content.
- Perform data annotation and labeling tasks with precision.
- Ensure data quality through rigorous evaluation and quality assurance processes.
- Work independently while adhering to strict guidelines regarding the use of AI tools.
- Collaborate with team members to enhance data processing methodologies.
Requirements
- Proficiency in English at B2, C1, C2, or Native level is required.
- Experience in AI and data capabilities is preferred.
- Familiarity with machine learning tasks and data preprocessing.
- Strong skills in data evaluation and quality assurance.
- Ability to work independently and manage time effectively.
Nice to Have
- Previous experience in a similar role or industry.
- Knowledge of data annotation tools and software.
- Understanding of AI technologies and their applications.
What We Offer
- Flexible work schedule that accommodates various lifestyles.
- Opportunity to earn extra income while working from home.
- Timely payments for your contributions.
- Supportive team environment with opportunities for growth.
- Ideal position for students, part-timers, or stay-at-home parents.
This remote AI Data Specialist position at RWS offers flexible hours and a competitive pay rate of $18/hour. Ideal for students and part-timers looking to gain experience in AI and data.
Who Will Succeed Here
Proficient in data annotation tools such as Labelbox or Prodigy, with a keen eye for detail to ensure high-quality datasets for machine learning models.
Self-motivated and disciplined, able to manage a flexible part-time schedule while maintaining productivity and meeting deadlines in a remote work environment.
Familiar with machine learning concepts and frameworks like TensorFlow or PyTorch, demonstrating a proactive approach to learning and applying ML principles to data evaluation tasks.
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