English Language Arts Curriculum Annotator (Elementary)

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We connect skilled contributors with real projects that shape how AI systems learn and behave—helping people start and grow careers teaching AI.

This project is managed directly with the end client through OpenTrain; you'll apply, onboard, and submit work on the platform while collaborating with the client for guidelines and quality reviews.

About AI training work in education

AI training (also called data labeling or annotation) is the human work behind smarter models. In education projects, contributors evaluate model outputs against curriculum goals so AI can produce accurate, grade-appropriate instructional content.

These roles are often fully remote and flexible—ideal for teachers who want meaningful side income while directly influencing the next wave of educational tools.

The role

We are hiring elementary English Language Arts annotators for a 3–6 month, fully remote, U.S.-based contract. You'll evaluate and rate AI-generated text against elementary ELA curriculum objectives and help build high-quality labeled datasets used to train instructional AI.

Two contributor tiers are available: Expert Annotators (audit outputs, co-author guidelines, curate reference data) and Standard Annotators (label examples, validate once protocols are finalized). Work is 100% online and scheduled by you, with ongoing quality assurance.

• Commitment: minimum 10 hours/week; project runs approximately 3–6 months
• Pay: $35 per hour (PAY_PER_HOUR, USD)
• Work type: contractor, part-time, fully remote; project managed via OpenTrain
• Data type: TEXT; label type: evaluation/rating; labeling software: provided

What you'll do

Tasks differ by tier but center on evaluating AI-generated ELA content and applying curriculum-aligned judgments to create reliable training data.

Expect to work in web-based annotation interfaces and follow rubric-based scoring protocols; guidelines and examples will be provided and refined during the project.

• Expert Annotators: audit AI outputs, co-author and refine annotation guides, curate reference examples, flag edge cases and ambiguous items
• Standard Annotators: label examples to established protocols, expand labeled datasets, participate in validation and quality checks
• Provide constructive feedback on model output and annotation rules to improve dataset quality
• Participate in continuous quality assurance and respond to guideline updates

Requirements

All applicants must be meticulous, comfortable providing constructive feedback, and able to commit at least 10 hours per week. Recent classroom experience is important for grounding judgments in U.S. elementary standards.

• Expert Annotator (required): 5+ years teaching English Language Arts in U.S. elementary classrooms; curriculum design, instructional coaching, or assessment-authoring experience; exceptional written communication; skilled at auditing annotations and refining guidelines
• Standard Annotator (required): at least 2 years recent elementary ELA classroom teaching; solid knowledge of current U.S. education standards; strong writing skills and careful attention to detail
• Both tiers: minimum 10 hours/week availability; familiarity with annotation tools or rubric-based scoring is a plus; comfortable flagging ambiguous/edge cases

Who should apply

This project is ideal for elementary teachers who want flexible, impactful contract work—during summer break or alongside the school year—helping shape how educational AI understands grade-level ELA.

Candidates must have U.S. elementary classroom teaching experience at the required tier. Recent teaching (within five years) is preferred for Standard Annotators.

• Teachers with curriculum-design or assessment experience are a strong fit for Expert roles
• Teachers with solid standards knowledge and classroom practice fit Standard roles
• Anyone excited to influence educational AI and comfortable with careful, rubric-driven evaluation

How it works

Apply through OpenTrain and complete the client onboarding steps. You will receive project guidelines, training examples, and access to the annotation interface. Work asynchronously on your schedule while meeting quality standards and time commitments.

Quality assurance reviews are continuous—expect feedback and occasional re-training on guidelines as the project matures. Payments follow the agreed hourly rate and contractor terms via the platform.

• Project length: ~3–6 months; flexible scheduling, remote work
• Minimum weekly commitment: 10 hours; typical workload is under 20 hours/week
• Hourly pay: $35 USD; paid per hour worked under contractor agreement