Job Description:
• Create high-quality instructional materials that teach modern data annotation and labeling workflows used to train and evaluate machine learning systems.
• Develop content across modalities—including text, image, video, audio/speech, and cross-modality labeling.
• Collaborate with internal program team to produce session plans, hands-on practice, examples, and assessments aligned to defined learning outcomes.
• Content should model best-in-class annotation behavior: rule-based decisions, clear rationales, consistent application of guidelines, and appropriate handling of ambiguity.
• Produce complete content packages per session/module, such as facilitator guide, learner materials, demos or walkthroughs, practice activities, strong vs. weak examples, rubrics/evaluation criteria, and short knowledge checks/assessments.
• Create hands-on exercises using a common annotation platform, including task setup guidance, labeling instructions, example labels, edge cases, and review workflows.
• Review and iterate on content based on internal feedback and peer review.
• Participate in weekly and ad hoc meetings with the program team to align on objectives, standards, and delivery constraints.
• Support content deployment into our learning platform (training provided).
Requirements:
• Demonstrated experience creating machine learning training content, instructional content, curriculum materials, or technical content for adult learners.
• Hands-on experience as a data annotator, including using tools such as Label Studio or similar annotation platforms.
• Ability to translate complex content into clear, learner-friendly lessons with concrete examples.
• Strong command of English (written and verbal) with excellent attention to detail and consistency.
• Organized, deadline-reliable, and comfortable working in a remote, fast-moving environment.
• Nice to have: Experience creating content across multiple data modalities (text, image, video, audio) and/or cross-modality tasks.
• Experience building rubrics, scoring guides, or evaluation criteria for annotation quality.
Benefits:
• 100% free training programs for learners
• Equal opportunity employer and commitment to providing equal opportunity for all
• Commitment to full inclusion of all qualified individuals
• Supportive, human-led group learning environments
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