At a Glance
- Tasks: Evaluate AI outputs and create realistic K-12 education scenarios.
- Company: Join a leading AI research lab with top-tier investors.
- Benefits: Earn up to $1,000 per task with performance bonuses.
- Other info: Flexible hours and opportunities for career growth.
- Why this job: Make a real impact in education while working remotely.
- Qualifications: 3+ years in K-12 education and strong analytical skills.
About the Job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Position: K-12 Education Expert
Type: Contract
Compensation: $850–$1,000 per completed task
Location: Remote
Role Responsibilities:
- Review and evaluate AI-generated outputs related to lesson planning, student assessment, classroom management, and instructional design.
- Create realistic scenarios based on K-12 workflows such as IEP development, parent-teacher communication, and curriculum alignment to standards.
- Annotate, label, and validate data across K-12 use cases like differentiated instruction and formative assessment.
- Provide structured feedback on AI accuracy in pedagogical best practices and education regulations (IDEA, Title I, ESSA).
- Collaborate asynchronously with research teams to refine evaluation frameworks for K-12 education AI.
Qualifications Must-Have:
- 3+ years of professional experience in K-12 education (public, private, or charter).
- Background in classroom teaching, special education, school administration, district-level roles, or instructional coaching.
- Strong analytical thinking and ability to translate workflows into structured evaluation tasks.
- Clear written communication and attention to detail.
Compensation & Legal:
- Task Completion Pay: Competitive and based on task quality.
- Performance Bonus: Weekly bonus incentive for top performers.
- Hourly Opportunity: Transition to hourly compensation for sustained quality and throughput.
Application Process: (Takes 20–30 mins to complete)
- Upload resume
- AI interview based on your resume
- Submit form
Resources & Support:
For details about the interview process and platform information, please check: Interview Process
For any help or support, reach out to: support@mercor.com
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
K-12 Educator - Fully Remote | Upto $1000 Part-time employer: Mercor
Mercor is an exceptional employer for K-12 educators seeking a flexible and impactful role in the evolving landscape of AI in education. With a fully remote position, competitive compensation, and opportunities for performance bonuses, employees can thrive in a supportive work culture that values innovation and collaboration. The company fosters professional growth by allowing educators to contribute their expertise to cutting-edge projects while working alongside elite talent from top investors.
StudySmarter Expert Advice🤫
We think this is how you could land K-12 Educator - Fully Remote | Upto $1000 Part-time
✨Tip Number 1
Make sure to showcase your K-12 experience during the interview. We want to hear about your classroom successes and how you've tackled challenges in education. Bring real examples to the table!
✨Tip Number 2
Familiarise yourself with AI in education before your interview. We’re looking for someone who can evaluate AI outputs effectively, so understanding how AI impacts lesson planning and assessment is key.
✨Tip Number 3
Don’t forget to prepare questions for us! This shows your interest in the role and helps you gauge if we’re the right fit for you. Ask about our projects or how we support our educators.
✨Tip Number 4
Apply through our website for a smoother process. We review applications daily, so getting your application in early can give you an edge. Plus, it’s super easy to track your application status!
We think you need these skills to ace K-12 Educator - Fully Remote | Upto $1000 Part-time
Some tips for your application 🫡
Tailor Your Resume:Make sure your resume highlights your K-12 experience and skills that match the job description. We want to see how your background fits with what we're looking for, so don’t be shy about showcasing your relevant achievements!
Nail the AI Interview:The AI interview is a key part of our process. Take your time to answer questions clearly and thoughtfully. We’re looking for your insights and expertise in K-12 education, so let your passion shine through!
Be Detail-Oriented:Attention to detail is crucial in this role. When filling out the application form, double-check your entries for accuracy. We appreciate candidates who take the time to ensure everything is spot on!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into our hands quickly. Plus, it’s super easy and straightforward—just follow the prompts!
How to prepare for a job interview at Mercor
✨Know Your K-12 Stuff
Make sure you brush up on your K-12 education knowledge, especially around lesson planning and classroom management. Familiarise yourself with current educational standards and regulations like IDEA and ESSA, as these will likely come up in your interview.
✨Showcase Your Experience
Be ready to discuss your 3+ years of experience in K-12 education. Prepare specific examples from your background in teaching, special education, or instructional coaching that highlight your analytical thinking and ability to translate workflows into structured tasks.
✨Communicate Clearly
Since clear written communication is a must-have for this role, practice articulating your thoughts concisely. You might be asked to provide feedback on AI outputs, so being able to express your ideas clearly will set you apart.
✨Engage with the Team
As collaboration is key in this role, think about how you can demonstrate your ability to work asynchronously with research teams. Be prepared to discuss how you've successfully collaborated in the past and how you can contribute to refining evaluation frameworks.
