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Location
In office (Menlo Park)
Seniority
Staff · 6+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Oct 14, 2026. Meta scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Meta Platforms is an American technology company founded in 2004 as Facebook and renamed in 2021 to signal its investment in immersive computing. It operates the largest family of social and messaging applications in the world, comprising Facebook, Instagram, WhatsApp, Messenger and Threads, and earns almost all of its revenue from advertising sold against that audience. Headquartered in Menlo Park, California, the company also develops the open Llama language models and the Reality Labs division behind Quest headsets and Ray-Ban smart glasses.
Meta Superintelligence Labs (MSL) is dedicated to developing AI-powered experiences for consumers, leveraging Meta's cutting-edge models. We're seeking a Special Projects Lead to take on MSL's hardest operational and strategic challenges - scoping ambiguous problems, driving cross-functional execution, and delivering results on high-priority initiatives on behalf of the Chief AI Officer.

This role is for a highly strategic, execution-oriented operator who thrives in ambiguity, moves fast, and delivers at scale. You'll work across the MSL organization to identify what needs to get done, figure out how to do it, and make it happen - whether that's standing up a new process, driving a critical cross-org initiative, or solving a problem no one else has been able to crack.

Responsibilities

Own and execute MSL's highest-priority special projects end-to-end - from problem definition and stakeholder alignment through delivery and measurable outcomes. Take on emerging, ambiguous challenges that don't have a clear owner or playbook and drive them to resolution with speed and rigor. Develop project strategies, track execution against goals, and ensure accountability across workstreams. Drive collaboration across Legal, Finance, HR, Engineering, and other cross-functional teams to remove friction and advance project objectives. Build working relationships and navigate complex stakeholder landscapes to accelerate decision-making and unblock execution. Design and implement operational frameworks, processes, and communication structures that enable MSL to execute effectively as the organization scales. Identify operational gaps and inefficiencies, then build solutions that create leverage across the organization.

Qualifications

6+ years of proven experience in operations, strategic initiatives, program management, or a similar role within a fast-paced, complex organization Demonstrated ability to independently own and drive complex projects from ambiguity through execution and measurable results Experience managing multiple projects and priorities simultaneously, including stakeholder management, action tracking, and cross-functional coordination Excellent written and verbal communication skills, with the ability to draft executive briefs and presentations Proven track record of organizing, developing, and executing strategic projects that deliver results Experience in navigating C-Suite dynamics and company policies and procedures Familiarity with AI/ML concepts, applications, and industry trends sufficient to engage with technical teams and inform operational decisions Bachelor's degree or foreign equivalent Experience in adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience identifying and pursuing high-impact initiatives with limited direction, moving from problem identification to solution delivery with minimal oversight Experience in a special projects, strategic initiatives, or similar high-autonomy execution role MBA or foreign equivalent Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

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