Learning Commons, an initiative by Mark Zuckerberg and Priscilla Chan, aims to scale proven teaching and learning practices to benefit every learner. The organization seeks to translate learning science into classroom practice, accelerated by generative AI, and address the fragmentation in the edtech landscape by building open, public-purpose infrastructure (datasets, rubrics, resources) to raise the standard for educational tools and create more consistent, impactful learning experiences.
Requirements
- Experience building, training, and deploying AI/ML models, with a good understanding of deep learning methods.
- Expert 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.
Responsibilities
- Assist in design, develop, and deploy machine learning models and systems to address key educational use cases, taking ownership of specific features or small projects.
- Contribute to implementation and optimize techniques such as fine-tuning, Retrieval Augmented Generation (RAG), and other deep learning methods for applications in the education domain.
- Partner closely with tech lead, product managers, data scientists, staff engineers, and expert partners to understand requirements, iterate on solutions, and deliver impactful AI-driven features.
- 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 2 years of relevant industry experience in developing and applying machine learning methods.
- 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.
- The exact schedule will be at the hiring manager's discretion and communicated during the interview process.
- 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.
