Activities
historical
Alexandr Wang (born January 1997) is an American entrepreneur best known for co-founding Scale AI in 2016 and serving as its CEO. Raised in Los Alamos, New Mexico, the son of physicists, he demonstrated strong aptitude in mathematics and programming from a young age. After attending Los Alamos High School he briefly enrolled at the Massachusetts Institute of Technology (MIT) before leaving to pursue startup work.
Prior to founding Scale AI, Wang held early engineering roles including work at Addepar and Quora, and a brief stint in algorithmic roles. He launched Scale AI in 2016 to solve the AI industry bottleneck of high-quality labeled data and model evaluation tooling, originally focusing on autonomous vehicle datasets and computer-vision annotation.
Under Wang’s leadership Scale AI grew rapidly into a data-infrastructure company for enterprise AI customers, winning contracts across private and public sectors and raising multiple funding rounds that produced multibillion-dollar valuations.
present
As of 2025, Wang transitioned from day-to-day CEO responsibilities at Scale AI and took an executive role at Meta focused on advanced AI initiatives. He remained on Scale AI’s board while participating in broader policy and strategy efforts around national AI competitiveness and safety.
Wang is active in public discussions about the geopolitical implications of advanced AI, and has engaged with government and international leaders to advocate for accelerated AI investment and coordinated governance.
Connections to other people and companies
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Co-founder and former CEO: Scale AI (founding team and early investors)
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Close ties to enterprise AI customers and strategic partners in both industry and government
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Collaborates with senior AI leaders and researchers across multiple organizations, and in 2025 worked within Meta’s leadership on the companys superintelligence initiative
Expectations for the future
Wang has positioned himself at the intersection of AI productization, infrastructure, and policy. Given his move into a major industrial AI research organization, expect continued emphasis on large-scale data systems, model evaluation tooling, and rapid deployment of compute-backed research programs. His public statements and meetings with policymakers suggest he will be an active voice on national strategies for AI and on balancing rapid innovation with safety considerations.
Interests
Wang’s public comments and work indicate strong interests in:
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Scalable data infrastructure for machine learning
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Large models and the tooling needed to evaluate and validate them
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National competitiveness in AI and the geopolitics of technology
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Engineering-driven, execution-focused company building
Sources
Summary compiled from multiple reputable news reports and public profiles (industry press, major business publications, and publicly available biographical summaries). Specific source types consulted include major business outlets, technology press, and encyclopedic entries.