About the job
About Us
At Mathspace, we are dedicated to revolutionizing the way mathematics is taught and learned. Our belief is that with the right support, every student can thrive in mathematics. We are on a quest to develop the most advanced, adaptive platform to facilitate this transformation.
For over a decade, we have been at the forefront of creating interactive, feedback-rich math learning experiences that are embraced by hundreds of thousands of students and educators around the globe. Yet, our journey is just beginning.
The future of mathematics education involves leveraging AI to provide personalized, real-time assistance to every learner, akin to having a tutor available at all times. We are committed to making this vision a reality.
Join a passionate team that merges profound educational insights with state-of-the-art technology. Your contributions at Mathspace will have a direct impact on shaping how future generations engage with learning.
About the Role
As an AI Product Engineer with Mathspace, you will spearhead the creation of intelligent learning experiences driven by large language models (LLMs) and other generative AI technologies. From the initial concept to production deployment, you will craft innovative product features that provide students with timely hints, interactive feedback, and human-like math support on a large scale.
You will collaborate with a dynamic, cross-functional product squad composed of engineers, designers, educators, and product managers, exploring the possibilities at the intersection of pedagogy and AI. Your responsibilities will include evaluating models, designing prompts and evaluation frameworks, and ensuring polished experiences reach classrooms worldwide.
As we embark on this exciting AI journey, your insights will be pivotal in shaping our strategy, systems, and culture surrounding LLM development.
What You’ll Be Doing
- Designing and developing AI-driven learning experiences that incorporate LLMs into Mathspace’s applications for students and educators.
- Prototyping, testing, and rolling out LLM-based features, including math-specific feedback, adaptive hints, automated question generation, and tools for teachers.
- Working across the technology stack utilizing React, TypeScript, Python, and GraphQL.
- Experimenting with strategies such as prompting, RAG, vector search, and fine-tuning to enhance student learning outcomes.
- Collaborating with curriculum and pedagogy teams to ensure our AI solutions are pedagogically robust and aligned with our educational values.
- Contributing to our AI infrastructure and LLMOps processes, focusing on evaluation pipelines, prompt versioning, and observability tools.
- Thinking critically about the roles LLMs should play in education, and designing safeguards to enhance their effectiveness.
