Director, AI Manufacturing Enablement
Listed on 2026-11-01
-
IT/Tech
AI Engineer (Applied/Software), AI Business & Operations
Meta’s Manufacturing Engineering & Operations (MEO) organization is responsible for bringing Reality Labs’ most ambitious hardware products to life oss our functions — Manufacturing Operations, DFx, Manufacturing Test Engineering, and Quality — hundreds of workflows involve data analysis, decision-making, documentation, and cross-functional coordination that are ripe for AI-driven transformation.
We are seeking a Director, AI Manufacturing Enablement to lead a dedicated team that systematically identifies, prioritizes, and deploys AI and automation solutions across the MEO organization and its adjacent partners. This leader will operate at the intersection of manufacturing domain expertise and applied AI, delivering measurable productivity gains, quality improvements, and workflow automation across real production environments.
This is a founding leadership role reporting to the Director of MEO. You will build the team, define the AI strategy for manufacturing, and serve as the connective tissue between Meta’s broad AI capabilities and the practical realities of hardware manufacturing.
Director, AI Manufacturing Enablement 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
Minimum 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…
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).