Learning Commons, an initiative by Mark Zuckerberg and Priscilla Chan, aims to scale proven teaching and learning practices. The challenge is to translate learning science into classroom practice and accelerate this translation with generative AI. The edtech landscape is fragmented, and AI needs to be grounded in research, high-quality data, and expert evaluation to be effective. Learning Commons is building open, public-purpose infrastructure to raise the standard for educational tools and create more consistent, impactful learning experiences.
Requirements
- Solid experience building, training, and deploying AI/ML models, with a good understanding of deep learning methods.
- Proficiency in programming languages commonly used in ML (e.g., Python) and familiarity with relevant ML frameworks and libraries.
- Experience in translating ML research or prototypes into functional software and features.
- Ability to execute on a diverse range of work and own small projects or features within a larger system, often with little day-to-day guidance.
Responsibilities
- Design, develop, and deploy machine learning models and systems to address key educational use cases, taking ownership of specific features or small projects.
- Implement and optimize techniques such as fine-tuning, Retrieval Augmented Generation (RAG), and other deep learning methods for applications in the education domain.
- Collaborate closely with product managers, data scientists, staff engineers, and expert partners to understand requirements, iterate on solutions, and deliver impactful AI-driven features.
- Contribute to the development of multi-modal AI systems and ensure their scalability and reliability.
- Stay current with new developments in AI/ML research and identify opportunities for their practical application within the team's projects.
- Write robust, well-tested, and maintainable code, and participate actively in code and design reviews.
Other
- Enjoy working in a highly interactive and cross-functional collaborative environment with a diverse team of colleagues and external partners.
- Typically, a minimum of 5 years of relevant industry experience in developing and applying machine learning methods.
- Strong problem-solving skills and the ability to work effectively in a highly interactive, cross-functional, and collaborative environment.
- This role is a hybrid position requiring you to be onsite for at least 60% of the working month, approximately 3 days a week, with specific in-office days determined by the team’s manager.
- If you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.
