
Founding AI Engineer
7 days ago
Join to apply for the Founding AI Engineer role at Edexia (YC W25)
Join to apply for the Founding AI Engineer role at Edexia (YC W25)
This range is provided by Edexia (YC W25). Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range$80,000.00/yr - $200,000.00/yr
About Edexia
Edexia is on a mission to fix the mess we call the education system. We're starting with assessment—the area that places the greatest burden on educators and offers the most immediate impact for positive change. By revolutionising how assessment works, we're creating a cascade of improvements that will transform education from the ground up.
While others in EdTech are content with wrapping a basic UI around existing LLMs, we're taking the opposite approach—building sophisticated AI systems that actually solve the hardest problems in education (look at "What You'll Build" to find out more).
Our vision extends far beyond assessment. We're creating the foundation for systemic educational change, addressing the fundamental misalignments and inefficiencies that have plagued schools for generations. We've already secured contracts with schools across Australia and the US. We raised $4M USD at a $35M valuation after completing Y Combinator.
About Us
We're a small, focused 3-person team based in Brisbane, Australia. The CEO, Daniel Gibbon, and CTO Nathan are both second-time technical founders who previously built an EdTech to $200k ARR at 18 in just 1 year while achieving a perfect GPA. Now we are all on a mission to rebuild the education system from the ground up with AI.
This Job is Perfect for You If
- You're excited about solving challenging technical problems that have direct, meaningful impact on education and are willing to work relentlessly toward a central vision.
Must Haves
- Be incredibly smart, good at solving complex problems, and learning new things quickly.
- Be willing to work relentlessly to accomplish a vision of rebuilding our education system from the ground up with AI.
- Genuinely care about having a positive impact through your career.
- Have good baseline life and work habits and a willingness to relentlessly optimise every aspect of your life to maximise your productivity and fulfilment.
- Have some form of technical background, even if that is just math or physics.
- Have the confidence to keep pace with some of the smartest, most driven people in the world.
- Domain expertise in software engineering.
- Domain expertise in AI/ML.
- Domain expertise in education.
- Historical achievement that backs up your intellectual abilities (e.g. IMO/IOI medals).
As part of our team, you'll work on aspects of these challenges that both:
- Move the needle most significantly for our company and mission
- Align with your interests and strengths—whether that's core AI architecture, UI/UX design, reinforcement learning systems, or data pipeline engineering
- The Human-AI Alignment Problem: Interpreting Rubrics
Solutions:
- Rubric unpacking workflow to make a sophisticated initial guess of the interpretation
- Real-time voice AI rubric training coaches that have conversations with teachers to align on interpretation
- Reinforcement learning components that extract patterns from teacher corrections
- The Complex Marking Process: Accurately Evaluating Student Work
Solutions:
- Multi-agent workflows that break down complex assessment tasks into processing, identification, analysis, and communication
- OCR and computer vision systems that can handle diverse formats
- Task-specific analysis modules for different types of evaluation
- Systems for converting AI judgments into clear, actionable feedback
System architecture level: Breaking down complex problems into flexible multi-agent infrastructures that subdivide the work intelligently
- End-to-end evaluation frameworks to test complete performance
- Unit-level testing for each component and decision point
- First, we evaluate and combine existing models on the market in intelligent ways
- We experiment with different task decompositions and prompting techniques
- When needed, we explore fine-tuning and reinforcement learning from feedback
- As a last resort, we develop our own custom models for specific tasks
Tech Stack
- Python for AI development and model integration
- Various LLM APIs (OpenAI, Anthropic, etc.)
- Custom OCR and computer vision components
- Reinforcement learning frameworks
- Web technologies for the frontend (handled primarily by our CTO)
- Cloud infrastructure for deployment and scaling
- Seniority levelEntry level
- Employment typeFull-time
- Job functionEngineering and Information Technology
- IndustriesEducation
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