Meta is hiring a director of AI manufacturing enablement. This is a founding leadership role reporting to the director of manufacturing engineering and operations. It will build a dedicated team from the start.
Meta’s manufacturing engineering and operations organization brings Reality Labs hardware products to life at scale. Across manufacturing operations, design for excellence, manufacturing test engineering, and quality, hundreds of workflows involve data analysis, decision-making, and documentation. Those workflows also involve cross-functional coordination that is ripe for AI-driven transformation.
The leader will operate at the intersection of manufacturing domain expertise and applied AI. The goal is measurable productivity gains, quality improvements, and workflow automation. It must work across real production environments, not AI demos with no factory use.
Overview
| Detail | What the listing states |
|---|---|
| Employer | Meta |
| Location | Many US locations, see location note below |
| Pay | $245,000-$309,000 per year plus bonus, equity, and benefits |
| Job type | Full-time, founding leadership role |
| Shift | Not stated in supplied listing |
What you will do
- Conduct systematic workflow audits across all manufacturing engineering and operations functions to identify high-value AI and automation opportunities
- Develop and maintain an AI opportunity roadmap prioritized by impact, feasibility, and strategic alignment
- Scout adjacent organizations, including software engineering, data science, extended reality technology, and production engineering, for tools, models, and frameworks that can be adapted for manufacturing
- Stay current on Meta internal AI platform capabilities, including large language models, computer vision, anomaly detection, and generative AI, and translate them into manufacturing applications
- Build and ship AI-powered tools, including automated defect classification, AI-assisted design for excellence 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, including time saved, error reduction, and decision quality improvement, and own the lifecycle from problem definition through production deployment and iteration
- Build partnerships with Meta AI and machine learning infrastructure teams, 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 and machine learning engineers and manufacturing-domain technologists
- Establish frameworks for build, buy, or adapt decisions for AI tools, and build a team culture of rapid prototyping, user-centric design, and measurable impact
What the employer asks for
- 12 or more years of experience across manufacturing or operations and applied AI, machine learning, or 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 or machine learning solutions in production environments, or diverse leadership experience leading complex operations through changes involving technology to improve productivity and quality of decision making
- Understanding of manufacturing workflows, including assembly, test, quality, and supply chain, and where AI adds genuine value
- Experience building and leading technical teams that ship products or 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 degree in Computer Science, Industrial Engineering, Manufacturing Engineering, or a related technical field, or equivalent practical experience demonstrated through leading process transformation, automation, or applied technology deployment in a manufacturing or operations environment
Pay and benefits
- Base pay range of $245,000 to $309,000 a year, plus bonus, equity, and benefits, according to the public compensation in the listing
How to apply
Meta lists one director role across many locations, not many different director jobs. Count it once, then check which location still lists the role.
Meta locations in the supplied list start with Charleston WV, Saint Paul MN, Augusta ME, and Helena MT. They also include Carson City NV, Columbus OH, Salem OR, and Salt Lake City UT. The remaining locations are Montpelier VT, Madison WI, Olympia WA, Oklahoma City OK, Pierre SD, Raleigh NC, and Nashville TN.
Search the Meta careers site for the exact title, Director, AI Manufacturing Enablement. Filter by the location you can actually work from. Do not apply to every location copy as if each one were a separate job.
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Frequently asked questions
Is this one job or many jobs at Meta?
It is one director role listed across many locations in the supplied set. Locations for the same title include Charleston, Saint Paul, Augusta, Helena, Carson City, Columbus, and Salem. They also include Salt Lake City, Montpelier, Madison, Olympia, Oklahoma City, Pierre, Raleigh, and Nashville.
Do I need both manufacturing and AI experience?
Yes, in balance. The listing asks for 12 or more years across manufacturing or operations and applied AI, machine learning, or automation. You need depth in one area, fluency in the other, and leadership experience of 5 years or more.
Can a degree be replaced by experience?
Yes, in part. The listing allows a bachelor degree in a related technical field, or equivalent practical experience. That experience must come from leading process transformation, automation, or applied technology deployment in a manufacturing or operations environment.
What is the pay?
The public compensation in the listing is $245,000 to $309,000 a year, plus bonus, equity, and benefits.
Sources
- Supplied Meta listing, seen October 28, 2026 – No apply URL was supplied, so none is linked here. Multiple location copies in the supplied set are treated as one role in this post.
- Federal Trade Commission, Job Scams – Federal Trade Commission guidance that honest employers never ask you to pay to get a job. Verify this link in a browser before publishing.
Disclaimer: Pay, shift, and deadline figures in this post come from the supplied listing seen on October 28, 2026. Listings change fast, so check the original employer posting before you apply. No apply URL was supplied with this listing, so none is linked here.
[Author Needed] Author name, role, and bio were not provided for this post. No author credentials are claimed here.
Date published: October 28, 2026.
