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Director, AI Manufacturing Enablement

Meta· Program Management
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Hybrid (Sunnyvale, CA)$245k - $309kFull-timePosted 1mo ago

About the role

Director level role leading a dedicated team to identify, prioritize, and deploy AI and automation solutions across Meta's Manufacturing Engineering & Operations (MEO) to improve productivity, quality, and workflow automation in hardware manufacturing environments.

Responsibilities

  • Conduct systematic workflow audits across all MEO functions to identify high-value AI/automation opportunities — categorized by efficiency gain, quality improvement, or full automation potential
  • Develop and maintain an AI opportunity roadmap prioritized by impact, feasibility, and strategic alignment
  • Scout adjacent organizations (SW Engineering, Data Science, XRT, Production Engineering) for existing tools, models, and frameworks that can be adapted for manufacturing use cases
  • Stay current on Meta's internal AI platform capabilities (LLMs, computer vision, anomaly detection, generative AI) and translate them into manufacturing applications
  • Build and ship AI-powered tools for MEO workflows including automated defect classification, AI-assisted DFx review, predictive yield modeling, intelligent test sequencing, natural language interfaces for manufacturing data queries, and automated reporting and documentation
  • Define success metrics for each deployment (time saved, error reduction, decision quality improvement) and own the end-to-end lifecycle from problem definition through production deployment and iteration
  • Build partnerships with Meta's AI/ML infrastructure teams to leverage internal platforms and partner with Manufacturing Test Engineering on AI-enabled test optimization
  • Collaborate with contract manufacturers on AI readiness, data infrastructure, and tool deployment at factory sites
  • Recruit, hire, and develop a team of applied AI/ML engineers and manufacturing-domain technologists
  • Build a team culture that values rapid prototyping, user-centric design, and measurable impact
  • Establish frameworks for evaluating build-vs-buy-vs-adapt decisions for AI tools

Qualifications

  • 12+ years of experience across manufacturing/operations and applied AI/ML/automation, with demonstrated depth in at least one and working fluency in the other, including at least 5 years in a leadership role
  • Experience deploying AI/ML solutions in production environments, or diverse leadership experience leading complex operations through changes involving the introduction of technology to improve productivity and quality of decision making
  • Understanding of manufacturing workflows — assembly, test, quality, supply chain — and where AI adds genuine value
  • Experience building and leading technical teams that ship products/tools iteratively
  • Experience operating in ambiguity — defining the problem space, not just solving well-scoped problems
  • Experience in process transformation and organizational change management — driving adoption of new tools and ways of working across engineering teams
  • Bachelor's degree in Computer Science, Industrial Engineering, Manufacturing Engineering, or a related technical field, or equivalent practical experience demonstrated through a track record of leading process transformation, automation, or applied technology deployment in a manufacturing or operations environment

Skills

Required:AI strategy for manufacturingAI/ML deployment in productionTechnical team leadershipManufacturing domain knowledge
Nice to have:Change management & process transformation
Last updated Oct 23, 2026. Interested? Apply on the company site.

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