Data Annotator - General Knowledge (Remote)

Job Title: Data Annotator - General Knowledge (Remote)
Location: Remote

Hours: Flexible; depends on assignment.
Pay: We use a task-based structure that ranges from $10-$50 per high quality submission. Rates vary depending on factors such as quality of work, project complexity, education level, background/experience (e.g. higher rates for specific fields of study).

Company Overview:
At Snorkel AI, we are pioneering new approaches to high-quality, human-in-the-loop data development for training, tuning, and evaluating AI models. As part of our growing team, you’ll contribute directly to AI advancements by helping us annotate,curate, and perform quality control reviews on large datasets. This is an exciting opportunity to contribute to cutting-edge approaches to data development, and push the data frontier of what modern LLMs do and don’t know. 

Role Overview:
Data annotation is the process of labeling or curating data to train, tune, and/or evaluate AI models. This includes tasks like identifying objects in images, tagging pieces of text, or generating multiple-choice questions to support AI models that depend on high-quality labeled data for accuracy. We are seeking detail-oriented Data Annotators to assist with these tasks, ranging from annotating multimodal data (text, images) to generating educational content such as questions.

This remote role allows for flexible, task-based work, providing opportunities for those who are self-motivated and efficient with their time to make a significant impact while controlling their earning potential.

Key Responsibilities:

Tasks will change project to project, but typically fall into the following buckets of work:

• Multimodal data annotation: Accurately label and tag data, including images and text, following provided guidelines.
• Multiple-choice question generation: Create clear and high-quality questions for educational or AI training purposes.
• Quality assurance: Review and verify your annotations to ensure consistency and correctness across datasets.

Skills and Qualifications:

• Some amount of college-level mathematics: Basic mathematical skills to understand complex concepts and work with technical data.
• Attention to detail: Precision is crucial, as incorrect labeling can impact the performance of machine learning models.
• English proficiency: Excellent written and verbal communication skills, especially for generating content and annotating text-based data.
• Data literacy: Experience or familiarity with handling and processing various types of data is preferred.
• Technical aptitude: Comfort with basic software tools, spreadsheets, or annotation platforms is beneficial.
• Self-motivation: Ability to work independently, manage time effectively, and meet project goals in a remote work environment.

What We Offer:

• Competitive and flexible pay that allows you to control your earnings
• The opportunity to work remotely from anywhere, with flexible hours.
• A chance to contribute to the development of cutting-edge AI technologies with world class AI/ML research teams

How to Apply:
Interested candidates should submit their resume. We will reach out with next steps to get started - no interviews are required, but our process will include completing a brief assessment, background check and onboarding session. If you would like to speak with a recruiter to learn more, we can arrange that as part of your process as well.