<h2>The Team</h2> At Learning Commons, we pair technology with grantmaking to scale proven teaching and learning practices to benefit every learner. We aim to translate what learning science tells us about how students learn best into classroom practice. With the advent of generative AI, that translation work can be accelerated and scaled to have a greater impact.  Our mission is to bring learning science into the tools used every day by teachers and students, ensuring that technology reflects the realities of classrooms and strengthens teaching and learning. In today’s fragmented edtech landscape, school districts are often left piecing together products that don’t always align with curricula or instructional needs. While AI holds enormous potential to support educators, it can only deliver on that promise when grounded in research, high-quality educational data, and expert evaluation. That’s why we’re building open, public-purpose infrastructure — datasets, rubrics, and resources — that help raise the standard for educational tools and create more consistent, impactful learning experiences for all students and teachers. At our core, we are builders, and our unique builder philanthropy approach is what sets us apart from other education funders. Take a closer look at the <a href="https://chanzuckerberg.com/education/impact/">highlights and significant milestones</a> of CZI’s first eight years of education work. <h2>The Opportunity</h2> Educators are already using AI-based tools in various ways—including generating lesson plans, creating classroom materials such as tests and assignments, and helping differentiate instruction for students. We are inspired and excited about the possibilities and promise of AI to accelerate the availability of research-backed practices at scale. We are actively and thoughtfully exploring how to incorporate AI into products in close partnership with researchers, experts, and educators. As a Machine Learning Engineer on the AI/ML team, you will play a crucial role in translating cutting-edge AI research and exploration into tangible tools and capabilities. Youll work on applying and scaling machine learning models to address specific educational challenges. You’ll have the opportunity to own significant features and contribute to the design of robust, scalable ML systems. <h2>What Youll Do</h2> <ul> <li>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.</li> <li>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.</li> <li>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.</li> <li>Stay current with new developments in AI/ML research and identify opportunities for their practical application within the teams projects.</li> <li>Write robust, well-tested, and maintainable code, and participate actively in code and design reviews.</li> </ul> <h2>What Youll Bring</h2> <ul> <li>Enjoy working in a highly interactive and cross-functional collaborative environment with a diverse team of colleagues and external partners.</li> <li>Typically, a minimum of 2 years of relevant industry experience in developing and applying machine learning methods. </li> <li>Experience building, training, and deploying AI/ML models, with a good understanding of deep learning methods.</li> <li>Expert in programming languages commonly used in ML (e.g., Python) and familiarity with relevant ML frameworks and libraries.</li> <li>Experience in translating ML research or prototypes into functional software and features.</li> </ul> <h2>Compensation</h2> The Redwood City, CA base pay range for a new hire in this role is $169,000 - $264,000. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.  <h2>Work Mode</h2> As we grow, we’re excited to strengthen in-person connections and cultivate a collaborative, team-oriented 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 managers discretion and communicated during the interview process. <h2>Benefits for the Whole You </h2> We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible.  <ul> <li>Provides a generous employer match on employee 401(k) contributions to support planning for the future.</li> <li>Annual benefit for employees that can be used most meaningfully for them and their families, such as housing, student loan repayment, childcare, commuter costs, or other life needs.</li> <li>Life of Service Gifts are awarded to employees to “live the mission” and support the causes closest to them.</li> <li>Paid time off to volunteer at an organization of your choice. </li> <li>Funding for select family-forming benefits. </li> <li>Relocation support for employees who need assistance moving to the Bay Area</li> <li><a href="https://chanzuckerberg.com/careers/#benefits">And more</a>!</li> </ul> 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. Explore our <a href="https://chanzuckerberg.com/careers/working-reimagined/">work modes</a>, <a href="https://chanzuckerberg.com/careers/#benefits">benefits</a>, and <a href="https://chanzuckerberg.com/careers/candidate-journey/">interview process</a> at <a href="https://www.chanzuckerberg.com/careers">www.chanzuckerberg.com/careers</a>. #LI-Hybrid <div><table> <tbody> <tr> <td> </td> <td> </td> <td><a href="https://www.facebook.com/chanzuckerberginitiative/" target="_blank"> </a></td> <td><a href="https://www.instagram.com/chanzuckerberginitiative/" target="_blank"></a></td> <td><a href="https://www.threads.net/@chanzuckerberginitiative/" target="_blank"></a></td> <td><a href="https://www.linkedin.com/company/chan-zuckerberg-initiative/" target="_blank"></a></td> <td><a href="https://twitter.com/chanzuckerberg" target="_blank"></a></td> <td><a href="https://www.youtube.com/channel/UCZioJ6fb9SuRdLIO7DlE09w" target="_blank"> </a></td> <td> </td> <td> </td> </tr> </tbody> </table> <h5> </h5></div>

Chan Zuckerberg Initiative

Machine Learning Engineer, Education

Chan Zuckerberg Initiative

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