Director of Learning $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 designed for the academic leader who chooses to architect the system rather than critique it from the sidelines. You bring subject-matter fluency sufficient to recognize high-quality learning, the discipline to codify that insight into rubrics and AI-driven quality mechanisms, and the pragmatism to respond decisively to incomplete data. Student improvement is what matters to you, and you accept accountability for that metric.
2 Hour Learning is pursuing an objective few in the software or education sectors dare to undertake. There are no teachers, no textbooks, and no safety net of traditional pedagogy beneath the product. AI serves as the operational framework. In this capacity, you will deploy it to produce and refine learning content, architect interventions, oversee quality, and advance the platform. The rhythm resembles high-performance tech, consulting, or finance more than traditional education, and the return is direct authority over a subject's student results across multiple campuses.
This position entails operating a function. You will construct AI-enabled learning ecosystem upgrades, respond to student-performance data with focused interventions, generate evidence-backed decision documentation, and lead a team measured by explicit benchmarks linked to MAP, AP, SAT, and ISEE outcomes. You will also collaborate closely with product, engineering, and data science to articulate the platform's next requirements. This role suits someone who instinctively turns to AI, conducts their own analysis, delivers under uncertainty, and assumes full ownership of results. It will frustrate anyone drawn to consensus-driven timelines, minimal accountability, or the security of established methods.
You will serve as a central leader within the academics team, wielding genuine influence over your subject's performance and the evolution of the broader learning infrastructure. Your colleagues will depend on your standards, your judgment, and your capacity to translate student data into action. If that prospect excites rather than overwhelms you, this role is likely built with you in mind.
What you will be doing
- Learning Ecosystem Enhancements — AI-powered 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 — Precision intervention strategies for underperforming students or cohorts, informed by MAP, AP, SAT, ISEE, and related performance metrics.
- Student Performance Decision Records — Systematic, evidence-grounded decisions that document student performance improvement actions, underpinned by dashboards, analytics, tickets, surveys, coaching calls, and assessment data.
- Learning Ecosystem Improvement Specs — Execution-ready specifications for product, engineering, and data science enhancements, featuring problem definitions, corroborating evidence, projected student impact, and acceptance criteria.
What you will NOT be doing
- Repackaging traditional education in an AI wrapper. This is not about reproducing classroom instruction through screens – we are fundamentally reconceiving learning from first principles.
- Analyzing data in a vacuum. You will be expected to engage routinely with K-12 students, treating their feedback as critical input from our paying customers.
- Waiting for consensus to push boundaries. You will advocate for a bold vision and mobilize others around data-informed results.
- Adhering to conventional methods. You will have the freedom to explore innovative approaches to motivation, assessment, and instruction.
- Fearing AI's impact on education. In this environment, you will leverage AI as a transformative tool to reimagine learning, not as a risk to be contained.
Key responsibilities
Lead innovation in AI-powered, teacher-less education to achieve outstanding student outcomes across multiple campuses. Combine data analytics with consistent student engagement to iteratively enhance 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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