EXPOSED
The core of this job — reading engineering drawings and turning metal or plastic stock into a working prototype on lathes, mills, grinders, and by hand fitting — is physical work in a shop that no current robot does end-to-end. The real pressure isn't LLMs, it's CAD/CAM and additive manufacturing: parts that once required a skilled model maker's hands are now printed or cut from a solid model, and design iteration happens in software before anything is made. There is no license, no signature requirement, and the buyer is an internal engineering team rather than a client paying for a relationship, so the moats are almost entirely craft and embodiment.
Part 2020 shock, part continued decline in the years since.
Median pay $57,020 → $63,340 -11.1% in real terms
This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.
So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.
BLS projection, 2024–2034
-18.2%
Percentage only. The projection counts a different population from the 2,610 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Shrinking, but not obviously because of AI
The BLS projects -18.2% by 2034, but at 50/100 this work is only moderately exposed — not the profile of a job current AI can simply do. Occupations shrink for many reasons, and the score does not point at automation as this one's cause.
Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.
~300 openings a year on average, including replacing people who leave.
ModelerDioramistFabricatorPrototyperTool MakerModel MakerForm BuilderMockup MakerTool BuilderDisplay MakerMandrel MakerModel BuilderMockup BuilderTemplate MakerPlastic ModelerProduct BuilderPattern FinisherMetal Model MakerScale Model MakerMetal Mockup MakerMetal Model BuilderFirearms Model MakerPrototype FabricatorModel Maker Machinist
Holding it up: embodiment . Weakest point: liability shield .
Mixed — a routine tier and a judgment tier Setting up a Bridgeport, indicating stock to a thou, hand-scraping a mating surface and dressing a scale model's compound curves still needs a person at the machine — but a large slice of your old work (making a one-off housing, a proof-of-concept bracket, a foundry pattern) now leaves the shop as an STL file to a printer or a 5-axis CNC, which is why this sits at 13 and not 17.
Hands-on in uncontrolled environments You work standing at lathes, mills, surface grinders and sanders with chips, coolant, solvents and 3D-printer resins around you, fitting and reworking parts by feel on stock that never arrives twice the same — the only thing keeping it off the top of the band is that the shop is climate-controlled and you aren't crawling through a plant or up a structure.
No licence, no signature requirement No state licence, no stamp, no certification gates model-making work; the engineer who signed the drawing owns the design and the QC inspector signs off the part, so nothing legally requires a specific credentialed human to have made it.
Meaningful discretion You choose fixturing, machining sequence, stock allowance and where to deviate from a drawing that can't actually be built, and a wrong call scraps expensive material or sends a flawed prototype into testing — but a designer or engineer reviews the result and the stakes are schedule and cost, not safety, which caps this below the top band.
The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.
Your task mix speaks to task resistance (13/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (1/20) is whether the law requires a licensed human to sign. Trust premium (7/20) is whether buyers specifically pay for a person. Judgment and accountability (12/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 20 of this occupation's 50 points (40%).
Embodiment (17/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
Sheet Metal Workers SAFE
The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 61/100, still EXPOSED.
Task-mix shift: as CAD/CAM and printing absorb the geometry-reproduction tier, the surviving work is the tier printers cannot do — hand-fitting mating surfaces, tolerance chasing on non-printable materials, tooling/fixture fabrication, and salvaging designs that fail first-article inspection. Watch for shop job postings that drop 'manual mill/lathe production' and foreground 'prototype problem-solving, first-article rework, fixture design'.
Displacement of the shield from the person to the artifact: FAA/ASME-style requirements where a prototype or master model used for airworthiness or pressure-vessel qualification must be fabricated and dimensionally verified under a named, qualified individual (cf. NADCAP special-process operator certification, AS9102 first-article reports signed by an identified operator). Also ITAR/defense work where a cleared US person must physically perform the build. This raises certification-and-signature weight, not personal tort liability — realistic move is small.
If the role formally owns first-article disposition — authority to reject a design as unmanufacturable, to call a use-as-is versus scrap decision, and to sign the AS9102 or PPAP dimensional report — the consequential call sits with the model maker rather than the design engineer. Watch for shops that give model makers named sign-off on first-article inspection reports.
Near ceiling already at 17. The only realistic route up is a shift of the work mix toward one-off, non-repeatable setups in unstructured shop space (repair of legacy tooling, oversized or mixed-material assemblies) where no fixturing exists for a robot cell to reference.
The limit. No plausible route to a meaningful trust premium: the buyer is an internal engineering team optimizing cost and lead time, not a client paying for a named human's hands. There is no licensing body and no realistic prospect of one for a 2,610-worker production occupation. Even with every lever above, this stays a craft-and-embodiment moat that erodes as additive manufacturing widens its material and tolerance envelope.
| Detroit-Warren-Dearborn, MI | 490 | $81,110 +28% |
| Los Angeles-Long Beach-Anaheim, CA | 120 | $94,950 +50% |
| New York-Newark-Jersey City, NY-NJ | 80 | $77,710 +23% |
| Dallas-Fort Worth-Arlington, TX | 70 | $89,960 +42% |
| Grand Rapids-Wyoming-Kentwood, MI | 70 | $44,220 -30% |
| Boston-Cambridge-Newton, MA-NH | 60 | $70,980 +12% |
| Providence-Warwick, RI-MA | 60 | $58,500 -8% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 40 | — |
| Los Angeles-Long Beach-Anaheim, CA | 120 | $94,950 +50% |
| Dallas-Fort Worth-Arlington, TX | 70 | $89,960 +42% |
| San Francisco-Oakland-Fremont, CA | 40 | $84,780 +34% |
We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.
That is worth saying out loud next to a score of 50. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.