Learning Designer $200,000 USD/year Pay is set based on global value, not the local market.
Most roles = hourly rate x 40 hrs x 50 weeks
Description
This role is for academic leaders who prefer building systems to analyzing them from the sidelines. You bring subject-matter fluency that lets you recognize high-quality learning, the rigor to translate that insight into rubrics and AI-powered quality mechanisms, and the pragmatism to act quickly on imperfect data. Student improvement matters to you, and you are prepared to be measured by that standard.
2 Hour Learning is attempting what few in software or education dare to try. Teachers, textbooks, and the familiar scaffolding of traditional instruction are absent. AI is the foundation. In this position, you will leverage it to produce and refine learning content, design interventions, track quality, and advance the platform. The rhythm resembles high-performance tech, consulting, or finance more than traditional education, and the reward is direct ownership of student outcomes in your subject across multiple campuses.
This position centers on operating a function. You will develop AI-powered enhancements to the learning ecosystem, respond to student performance signals with focused interventions, produce evidence-based decision documentation, and lead a team against explicit standards linked to MAP, AP, SAT, and ISEE performance. You will also collaborate closely with product, engineering, and data science to determine the platform's next requirements. It suits someone who defaults to AI, handles analysis independently, ships work amid uncertainty, and takes full ownership of results. Anyone who prefers consensus-driven timelines, minimal accountability, or established systems will find it frustrating.
You will serve as a core leader within the academics team, wielding meaningful influence over your subject's performance and the broader learning system's evolution. Your colleagues will depend on your standards, your judgment, and your capacity to translate student data into action. If that prospect feels energizing rather than daunting, this role is likely designed for you.
What you will be doing
- Learning Ecosystem Enhancements — AI-generated refinements to subject-specific K–12 learning experiences spanning content, adaptive pathways, and student interventions, shaped by student feedback, analytics, assessments, and coaching insights.
- Data-Driven Academic Interventions — Focused intervention strategies for students or cohorts falling behind, informed by MAP, AP, SAT, ISEE, and related performance metrics.
- Student Performance Decision Records — Repeatable, evidence-backed decisions that document actions taken to improve student performance, supported by dashboards, analytics, tickets, surveys, coaching calls, and assessment data.
- Learning Ecosystem Improvement Specs — Implementation-ready specifications for product, engineering, and data science enhancements, featuring problem statements, supporting evidence, anticipated student impact, and acceptance criteria.
What you will NOT be doing
- Repackaging traditional education in an AI wrapper. This isn't about replicating classroom instruction via screens – we're fundamentally reimagining learning from the ground up.
- Analyzing data in isolation. You'll be expected to regularly engage with K-12 students, valuing their feedback as essential input from our paying customers.
- Waiting for consensus to push boundaries. You'll champion a bold vision and rally others around data-driven results.
- Sticking to conventional methods. You'll be free to experiment with innovative approaches to motivation, assessment, and instruction.
- Fearing AI's impact on education. Here, you'll harness AI as an exciting tool to revolutionize learning, not as a threat to be mitigated.
Key responsibilities
Drive innovation in AI-powered, teacher-less education to achieve exceptional student outcomes across multiple campuses. Combine data analytics with consistent student engagement to continuously refine our learning ecosystem, measured by AP exam performance and MAP assessment growth.
Candidate requirements
- Master's degree or higher in Educational Science, Learning Science, Psychology, Psychometrics, Instructional Design, or a related field
- At least 5 years of experience in academic or EdTech leadership roles, with direct people management responsibility (hiring, performance evaluation, coaching, termination decisions)
- Demonstrated experience using AI tools as part of day-to-day professional workflows, and willingness to rely on AI extensively to improve academic and operational outcomes.
- Strong understanding of learning science principles, such as Cognitive Load Theory and Mayer's Multimedia Principles, and data-driven educational approaches
Applying for a role? Here’s what to expect.
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