Learning Designer, 2 Hour Learning

100,000 USD/year Pay is set based on global value, not the local market. Most roles = hourly rate x 40 hrs x 50 weeks ($50 USD/hour) Many ELA curriculum positions focus on creating lesson plans, assignments, and tests. This role centers on leveraging AI and student performance data to systematically refine how learners achieve mastery in reading, writing, vocabulary, language, and evidence-based reasoning. At 2 Hour Learning, students engage with an AI-driven learning model designed to accelerate progress beyond what conventional schooling permits. The objective is not producing polished curriculum documents. This is applied academic design. You will employ LLMs, AI-enhanced tools, no-code automation, agentic AI systems, and artifacts of student work to rebuild reading exercises, writing frameworks, vocabulary sequences, scaffolding structures, interventions, rubrics, prompts, and content validation processes. What you will be doing Identify persistent ELA learning obstacles through analysis of student performance data, platform analytics, assessment outcomes, writing samples, reading responses, and completed assignments. Deploy AI tools and agentic workflows to redesign reading exercises, writing frameworks, explanations, vocabulary sequences, grammar drills, scaffolding, and targeted interventions. Refine ELA assessments by revising question stems, writing prompts, incorrect answer options, rubrics, model responses, answer rationales, and supplementary materials. Review AI-generated or AI-modified content for clarity, academic rigor, alignment with source texts, grade-appropriateness, instructional effectiveness, and consistency with Alpha's learning science framework. Apply evidence from MAP, SAT, AP, platform performance, and internal evaluations to determine which content requires updating, replacement, or complete reconstruction. What you will NOT be doing Creating standalone worksheets, lesson plans, or test preparation resources disconnected from student learning data. Operating a traditional classroom, manually grading essay submissions, or overseeing school administrative functions. Developing education software products. Conducting high-level education strategy from a remove.

Key responsibilities
Drive quantifiable ELA mastery gains by systematically refining reading, writing, language, assessment, scaffolding, and intervention content informed by student learning evidence. Candidate requirements Bachelor's degree or higher in English, Literature, Linguistics, Writing, Reading Education, English Education, Instructional Design, Cognitive Science, or a closely related field. 3+ years of experience in ELA instruction, literacy curriculum development, assessment development, educational content creation, or learning design. Demonstrated K-12 ELA expertise, including the ability to evaluate reading comprehension, writing quality, language accuracy, text complexity, sequencing, and grade-level appropriateness. Practical knowledge of learning science or instructional design principles, such as mastery learning, direct instruction, scaffolding, cognitive load, and retrieval practice. Experience using AI tools to improve educational work, including LLMs, AI-assisted content generation, no-code workflows, agentic AI tools, or coding/API-based tools. Ability to use student learning data and student work to identify ELA gaps and improve curriculum, assessments, scaffolds, or interventions. Nice to have Direct LLM API experience for content generation, data analysis, adaptive learning, or assessment improvement. Experience building an online audience or public knowledge base around literacy, writing, education, or AI. How much English do I need? Meet some people who've landed similar jobs As a single mom navigating life in Georgia (the country), Julia needed more than just a remote job
- she needed purpose and flexibility. After years of late nights as a fitness coach left him exhausted and disconnect... Watch Interview United States After years of giving everything to education, Sam De Palo was done. It's super hard to qualify
- extreme quality standards ensure every single team member is at the top of their game. Shortlist by skills, not bias We don't care where you went to school, what color your hair is, or whether we can pronounce your name. Join the world's largest community of AI-first remote workers. #