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
Not accepting applications on crossover.com at this time.
Description
This role is for the academic leader who would rather design the system than critique it. You possess the subject fluency to recognize high-quality learning, the rigor to translate that into rubrics and AI-driven quality controls, and the pragmatism to act quickly on incomplete data. Student improvement matters to you, and you accept being evaluated by that measure.
2 Hour Learning pursues what most software and education organizations avoid. There are no teachers, no textbooks, and no traditional instructional safety net beneath the product. AI serves as the operational foundation. In this position, you leverage it to produce and refine learning materials, design interventions, monitor quality standards, and advance the platform. The tempo resembles high-performance technology, consulting, or finance more than traditional education, and the reward is direct accountability for a subject's student outcomes across multiple campuses.
This position centers on operating a function. You will construct AI-powered enhancements to the learning ecosystem, respond to student-performance data with focused interventions, produce evidence-based decision documentation, and lead a team against explicit standards linked to MAP, AP, SAT, and ISEE outcomes. You will also collaborate closely with product, engineering, and data science teams to determine the platform's next requirements. It suits someone who defaults to AI, self-serves on analytical tasks, delivers despite uncertainty, and takes full ownership of results. It will frustrate anyone who prefers consensus-driven timelines, minimal accountability, or the security of established systems.
You will serve as a core leader within the academics team, wielding real influence over your subject's performance and the broader learning system's evolution. Your team will depend on your standards, your judgment, and your capacity to translate student data into action. If that prospect energizes rather than intimidates you, you are likely the candidate this role was designed for.
What you will be doing
- Learning Ecosystem Enhancements — AI-generated improvements to K–12 learning experiences specific to your subject, spanning content, adaptive pathways, and student interventions, informed by student feedback, analytics, assessments, and coaching insights.
- Data-Driven Academic Interventions — Focused intervention strategies for underperforming students or cohorts, guided by MAP, AP, SAT, ISEE, and related performance metrics.
- Student Performance Decision Records — Repeatable, evidence-backed decisions documenting 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 enhancements delivered by product, engineering, and data science, including 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 through 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, treating their feedback as critical input from our paying customers.
- Waiting for consensus to push boundaries. You'll champion a bold vision and mobilize others around data-driven outcomes.
- Sticking to conventional methods. You'll have the freedom to experiment with innovative approaches to motivation, assessment, and instruction.
- Fearing AI's impact on education. Here, you'll harness AI as a powerful tool to transform learning, not as a threat to be mitigated.
Key responsibilities
Drive innovation in AI-powered, teacher-less education to deliver exceptional student outcomes across multiple campuses. Integrate data analytics with regular student engagement to continuously refine our learning ecosystem, as 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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Prove real-world 
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Interview with the hiring manager.
Pass
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Accept job offer.
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