Instructional Designer $60,000 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
Consider this: Students complete a full day of academics in two concentrated hours, then spend afternoons launching podcasts, painting murals, or mastering back-handsprings. This is the 2-Hour Learning model that fuels Alpha Anywhere—and you're the architect who maintains its precision while engineering its next evolution.
From any location with reliable internet, you'll convert waves of AI-generated performance metrics into precise, timely interventions that guide every student toward 90% mastery and higher. When learners encounter obstacles, you'll join live coaching sessions, eliminate the barrier in the moment, and restore their momentum with renewed confidence. At the same time, you'll analyze dense streams of student achievement data, identifying hidden trends that release children's complete potential and building next-generation AI tools that may double learning velocity.
Parents observe rising self-assurance, students double their pace of learning, and you witness the immediate effect of each insight you generate, every AI system you automate, and every question you pose. Ready to convert data into acceleration for young learners? Continue reading.
What you will be doing
- Creating highly precise Academic Data Reports and performing systematic evaluation to identify problems, detect irregularities, and initiate corrections within 48 hours
- Delivering rapid-response intervention calls and facilitating post-assessment coaching to eliminate obstacles, distinguish knowledge deficits from mistakes, and sustain student motivation
- Assessing and deploying new educational applications and resources while prototyping AI/LLM solutions to advance learning methodologies and address specific challenges
- Collaborating with leadership to optimize tools, dashboards, and mastery benchmarks as the AI tutor advances
What you will NOT be doing
- Attending endless meetings or delivering generic presentation decks without clear visibility to actual results
- Grading papers, drafting lesson plans, or administering traditional educational programs—AI and innovation power our approach
- Functioning at high-level strategy without execution or becoming trapped in repetitive tasks—this position is hands-on and fluid
Key responsibilities
Accelerate student learning outcomes through AI-powered analysis and real-time academic intelligence, evidenced by improved metrics such as 2× learning velocity, app engagement, lesson comprehension, response accuracy, and diminished negative learning patterns across the Alpha Anywhere network.
Candidate requirements
- Proven experience in data science or comparable role, education, EdTech, or a student-support position with both analytical and interpersonal dimensions
- Competency in Google Sheets data analysis (lookups, pivot tables, filtering)
- High emotional intelligence, excellent communication abilities and a kid-friendly coaching approach
- Experience creating workflows and automations with AI
- At least 1 year experience working directly with K-8 students
- Available to work during required core hours of 8:00 AM to 12:00 PM Central Time, Monday through Friday.
Nice to have
- Foundation in learning science, educational theory, or documented success enhancing outcomes through data-driven approaches
- Experience with Generative AI, prompting methods, and foundational coding abilities (Python, JavaScript, etc.) for querying AI APIs
Applying for a role? Here’s what to expect.
Crossover's skill assessment process combines innovative AI power with decades of human research, to take the guesswork, human bias, and pointless filters out of recruiting high-performing teams.
Chat-style
screening interview.
Cognitive 
aptitude test.
Prove real-world 
job skills.
Interview with the hiring manager.
Pass
proctored test.
Accept job offer.
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Premium pay for premium talent
Over 50% of new hires double or triple their previous pay. Why? Because that’s what the best person in the world is worth.
Shortlist by skills, not bias
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