Director, AI Manufacturing Enablement

Meta; Sunnyvale (CA); On-site; USD 250,000 - 350,000; Full time

Job summary

Meta is seeking a Director of AI Manufacturing Enablement to lead a team that identifies, prioritizes, and deploys AI and automation across the MEO organization. This role sits at the intersection of manufacturing domain expertise and applied AI, delivering productivity gains in real production environments.

You will define the AI strategy for manufacturing, build the team, and serve as the connective tissue between Meta's AI capabilities and hardware manufacturing realities.

Qualifications

• 12+ years across manufacturing/operations and AI/automation with 5+ years in leadership.
• Experience deploying AI/ML solutions in production environments.
• Understanding of manufacturing workflows: assembly, test, quality, supply chain.
• Experience building and leading technical teams that ship iteratively.
• Ability to navigate ambiguity and define problem spaces.
• Experience in process transformation and change management across engineering teams.
• Bachelor's degree or equivalent practical experience in a technical field.

Responsibilities

• Lead AI manufacturing enablement across MEO and adjacent partners.
• Define AI strategy for manufacturing and operationalize solutions.
• Build and scale a high-impact AI/automation team.
• Bridge Meta's AI platforms with hardware production realities.
• Deliver measurable productivity gains and quality improvements.

Skills

AI strategy leadership

Manufacturing domain expertise

Data systems knowledge

Leadership of technical teams

Change management

Production AI deployment

Cross-functional collaboration

AI platforms familiarity

LLMs in industry

Time-series anomaly detection

Reinforcement learning in industry

Education

Bachelor's degree in CS/IE

Job description

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.

• 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
• 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