MLOps Lead, Central Technology

The Chan Zuckerberg Initiative was founded by Priscilla Chan and Mark Zuckerberg in 2015 to help solve some of society’s toughest challenges — from eradicating disease and improving education to addressing the needs of our local communities. Our mission is to build a more inclusive, just, and healthy future for everyone.

The Team

Founded by Priscilla Chan and Mark Zuckerberg in 2015, the Chan Zuckerberg Initiative (CZI) is a new kind of philanthropy that’s leveraging technology to help solve some of the world’s toughest challenges – from eradicating disease, to improving education, to reforming the criminal justice system. Our mission is to create a future for everyone.  Across our core Initiative focus areas of Science and  Education,  we’re pairing engineering with grantmaking, impact investing, policy work, and movement building, to help build an inclusive, just and healthy future for everyone.

Our Values 

• We believe we can help build a future for everyone. 
• We aim to be daring, but humble:  We look for bold ideas — regardless of structure and stage — and help them scale by pairing engineers with subject matter experts to build tools that accelerate the pace of social progress. 
• We want to learn fast, but build for the long-term: We want to iterate fast and help bring new solutions to the table, but we also realize that important breakthroughs often take decades, or even centuries. 
• Stay close to the real problems: We engage directly in the communities we serve because no one understands our society’s challenges like those who live them every day.  

Our success is dependent on building teams that include people from different backgrounds and experiences who can challenge each other's assumptions with fresh perspectives. To that end, we look for a diverse pool of applicants including those from historically marginalized groups — women, people with disabilities, people of color, formerly incarcerated people, people who are lesbian, gay, bisexual, transgender, and/or gender nonconforming, first and second generation immigrants, veterans, and people from different socioeconomic backgrounds.

The Opportunity

Our Central Tech team provides technology and security support for CZI, the Biohub Network,  and our grantees. We believe that Engineering and Security are most effective when in sync and learning from each other on a daily basis.  Our AI Infrastructure Engineering team enables our AI Research teams to achieve their goals faster and more securely. We leverage technology to automate manual processes, constantly innovate to optimize operations, provide first-class support, and build solutions to enable the scale and execution of our business partners' strategies and initiatives.

The AI/ML and Data Engineering Infrastructure organization works on building shared tools and platforms to be used across all of the Chan Zuckerberg Initiative, partnering and supporting the work of a wide range of Research Scientists, Data Scientists, AI Research Scientists, as well as a broad range of Engineers focusing on Education and Science domain problems. Members of the shared infrastructure engineering team have an impact on all of CZI's initiatives by enabling the technology solutions used by other engineering teams at CZI to scale. A person in this role will build these technology solutions and help to cultivate a culture of shared best practices and knowledge around core engineering.

What You'll Do

• Provide technical MLOps leadership: for a team of MLOps Engineers,  where you will manage and lead the team  in operating our heterogeneous AI training and inference systems as well as  collaborating in the design and build of our AI platform components.
• Drive the application of MLOps and DevOps principles: across our multiple platforms, ensuring peak operational efficiency across our AI operations and process automation necessary for a world class large scale AI model training environment. 
• Instrumentation and Observation technical leadership: for the MLOps team, defining our end to end metrics program including full proactive monitoring and alerting systems
• Facilitate model training through collaboration with our AI Researchers: alongside the rest of the AI Infrastructure Eng team work together to make sure that our models we are training and releasing to  inference make use of best machine learning and deep learning practices, and are through code automation libraries fully resilient to restarts and checkpoint recoveries. 
• Continuous Optimization of our Kubernetes based AI Lifecycle platform: through our IAC based practices and integrating our MLOps AI Lifecycle platform tooling, alongside integrating this with our On-Prem HPC systems into a cohesive heterogeneous platform. 
• Collaboration on Data systems