Director, AI Manufacturing Enablement

Meta • Olympia, WA • 3h ago

Summary:

Meta's Manufacturing Engineering & Operations (MEO) organization is responsible for bringing Reality Labs' most ambitious hardware products to life at scale. Across 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.

Required Skills:

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 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

Preferred Qualifications:

Experience with manufacturing data systems (MES, SPC, historian databases) and the data quality challenges they present

Experience in consumer electronics or precision hardware manufacturing environments

Familiarity with large-scale AI/ML platforms or similar large-scale AI platforms

Hands-on familiarity with LLMs, computer vision, time-series anomaly detection, or reinforcement learning in industrial settings

Track record of building new functions or teams from zero - particularly 'AI for X' teams embedded in non-AI organizations

Public Compensation:

$245,000/year to $309,000/year + bonus + equity + benefits

Industry: Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereo@types, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.

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