Instructional 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 new systems over critiquing existing ones. You bring subject-matter fluency to recognize excellent learning experiences, the discipline to translate that vision into rubrics and AI-driven quality mechanisms, and the operational agility to act decisively on incomplete data. Student growth matters to you, and you welcome being measured by it.
2 Hour Learning pursues an approach that few organizations in software or education dare to attempt. Teachers, textbooks, and traditional instructional scaffolding are absent. AI serves as the foundational operating model. In this capacity, you leverage it to produce and refine learning materials, design targeted interventions, oversee quality assurance, and advance the platform. The rhythm mirrors high-performance environments in tech, consulting, or finance rather than conventional schooling, and you gain direct accountability for student outcomes in your subject across multiple campuses.
This is a functional leadership position. You will architect AI-powered enhancements to the learning ecosystem, address student performance signals through focused interventions, generate evidence-backed decision documentation, and lead a team measured by MAP, AP, SAT, and ISEE performance. Collaboration with product, engineering, and data science teams will shape platform evolution. The role suits someone who instinctively turns to AI, independently conducts analysis, executes through uncertainty, and assumes full ownership of results. It will not suit those who favor consensus-driven timelines, minimal accountability, or reliance on established frameworks.
You will serve as a central leader within the academics function, wielding meaningful influence over subject-area performance and system-wide learning improvements. Your colleagues will depend on your standards, judgment, and capacity to translate student data into actionable steps. If that prospect excites rather than overwhelms you, this role was designed with you in mind.
What you will be doing
- Learning Ecosystem Enhancements — AI-powered refinements to K–12 subject-specific learning experiences, spanning content design, adaptive pathways, and student interventions, shaped by student feedback, analytics, assessments, and coaching observations.
- Data-Driven Academic Interventions — Focused intervention strategies for underperforming students or groups, informed by MAP, AP, SAT, ISEE, and comparable performance metrics.
- Student Performance Decision Records — Structured, evidence-backed documentation of actions taken to improve student outcomes, supported by dashboards, analytics, ticketing systems, surveys, coaching interactions, and assessment results.
- Learning Ecosystem Improvement Specs — Actionable specifications for product, engineering, and data science teams, detailing problem statements, supporting data, anticipated student impact, and success criteria.
What you will NOT be doing
- Wrapping traditional classroom models in digital packaging. This is not about screen-based replication of conventional instruction – we are redesigning learning from first principles.
- Working with data in isolation. Regular interaction with K-12 students is expected, with their feedback treated as critical input from our primary customers.
- Delaying action to secure broad agreement. You will advocate for ambitious goals and mobilize others through evidence-based results.
- Relying on established practices. You will have latitude to test novel approaches to motivation, assessment, and instructional delivery.
- Treating AI as a risk to be managed. In this environment, you will deploy AI as a transformative instrument to redefine learning.
Key responsibilities
Lead innovation in AI-driven, teacher-free education to produce outstanding student outcomes across campuses. Combine data analytics with consistent student interaction to refine the learning ecosystem continuously, with success measured by AP exam results and MAP assessment gains.
Candidate requirements
- Master's degree or higher in Educational Science, Learning Science, Psychology, Psychometrics, Instructional Design, or related discipline
- Minimum of 5 years in academic or EdTech leadership positions, including direct people management responsibilities (hiring, performance evaluation, coaching, termination decisions)
- Proven track record using AI tools in daily professional work, and readiness to leverage AI extensively to enhance academic and operational performance.
- Solid grounding in learning science frameworks, including Cognitive Load Theory and Mayer's Multimedia Principles, and data-informed educational methods
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