The Chan Zuckerberg Initiative (CZI) is looking to leverage AI and machine learning to accelerate the availability of research-backed practices at scale in education, aiming to equip educators, families, and students with tools that unlock the full potential of every student.
Requirements
- Typically, a minimum of 5 years of relevant industry experience in developing and applying machine learning methods.
- 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.
- 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.
- The exact schedule will be at the hiring manager's discretion and communicated during the interview process.
