← Risk register SOC 49-9043 · reviewed 2026-08-11

Maintenance Workers, Machinery

60,020 US workers · median $60,850/yr · Trades

EXPOSED

The core of this job — crawling into a press, feeling for bearing play, chasing a hydraulic leak, replacing a worn sprocket in a hot production line under time pressure — is physical diagnostic work in cluttered, unpredictable plant environments that today's robotics cannot touch. What AI does erode is the paperwork and diagnostic-lookup shell: work orders, PM scheduling, manual reference, vibration and sensor trend analysis, parts sourcing, and failure write-ups. The occupation is 'exposed' rather than 'safe' mainly because there is no licensure requirement and no client relationship to protect the role — the protection is purely that the work happens with hands on greasy metal.

10-year outlook: Employment holds roughly steady as plants automate production and need more people to keep that automation running, but the routine PM-round portion of the job shrinks into sensor-driven checklists, pushing pay and hiring toward workers who can rebuild and commission equipment, not just inspect it.

US employment, 2019–2025-17.7%
72,89060,020 workers

This fall is concentrated in 2020 and has not recovered since.

Median pay $47,520 → $60,850 +2.4% in real terms (nominal +28.1%, less ~25% US inflation over the period)

The job count is not the verdict

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

-2.8% 57,500 → 55,900 on the projections basis

Shrinking, but not obviously because of AI

The BLS projects -2.8% by 2034, but at 63/100 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.

~4,800 openings a year on average, including replacing people who leave.

One email if this score changes. Watch as many occupations as you like from the same address — no account, and nothing is sent on a schedule, only when a verdict actually moves.

Also known as — 24 job titles this covers

Titles reported by people doing this work, from the US Department of Labor's O*NET survey. If your job title is here, this page is about your work even though the name doesn't match.

DoperOilerDopemanGreaserHot ManShafterSalvagerShuttlerCar OilerCraftsmanMachinistPot LinerBelt FixerBelt LacerGrease ManHot WorkerLubricatorMaintainerMill OilerOverhaulerPot FluxerPump OilerRod FillerBox Builder

Score — 63/100 resistance

Holding it up: embodiment (19/20). Weakest point: liability shield (5/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 17 + 19 + 5 + 9 + 13 = 63. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 17/20

Tasks largely resist digitisation Repacking a bearing, shimming a misaligned coupling to within thousandths, hand-tightening a gearbox to spec, and tracking a hydraulic leak back through hose runs are tasks where the diagnosis lives in feel, sound and access — 17 rather than 20 because PM scheduling, lubrication route logging and CMMS-driven vibration trend calls are already being handed to sensors and software.

Embodiment 19/20

Hands-on in uncontrolled environments You work inside the machine — on your back under a conveyor, in the crawl space behind a press, on a ladder at a dust collector — in plants that are hot, loud, oily, LOTO-tagged and never laid out the way a robot needs, which is why this sits at 19 and not the 13-14 of shop-floor work done at a bench.

Liability shield 5/20

Certification preferred, not legally required There is no state licence to maintain machinery; you may hold a forklift cert, boiler or refrigerant card, or an OSHA 30, and the employer's maintenance supervisor and engineering sign off on the repair, so nothing in law makes you personally the one who answers for the machine — that puts this at 5, not 0.

Trust premium 9/20

Some relationship component Production supervisors call you by name because you know which line runs hot and which press has always had that vibration, and that plant-specific memory has real value — but it belongs to the site, not to you, and a new hire with the same skills replaces you inside a shift, which caps it at 9.

Judgment & accountability 13/20

Meaningful discretion You decide whether to run a line to end of shift or shut it down now, whether that noise is a bearing at 200 hours or 2 hours, and whether a temporary fix is safe enough to hold — real calls with production and injury consequences, held to 13 because engineering, the OEM manual and the manufacturer's specs set the boundaries you work inside.

Confidence: high · reviewed 2026-08-11 · how scoring works

What this job involves — and which parts are yours

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.

AI already does these at usable quality

These still need a person

Active moats on the surviving side: embodiment, judgment, physical-presence

How to future-proof this job

Where to go deeper on what this job runs on: edX — operations management and process monitoring courses free to audit · Apprenticeship.gov — industrial maintenance and millwright programs paid to train · MIT OpenCourseWare — circuits, systems and diagnostic method, free and ungated free · Apprenticeship.gov — paid, employer-sponsored trade apprenticeships, searchable by trade and ZIP paid to train · OSHA Outreach Training — the 10- and 30-hour cards most employers ask for low · Coursera — quality control and inspection courses, auditable free free to audit

All 35 skills ranked by how many jobs they open →

Where this experience transfers — nothing clears the bar

No occupation passed every test: close enough to maintenance workers, machinery on skills and subject matter, at least 10 points more resistant, no big jump in training, no new licence, no pay cut, and not shrinking on its own. That happens for 223 of the 654 occupations here that aren't SAFE, and it is worth stating plainly rather than leaving the section off.

The usual reason is that exposure travels with the skill profile. The jobs most similar to yours tend to be exposed for the same reasons yours is, so the near neighbours don't clear the gap — and the ones that do are a different kind of work, not a transfer of what you already know. Read that as a limit of this method, not a verdict that you're stuck: it only compares whole occupations, and it cannot see specialisation, industry, or anything you'd bring that isn't in a federal skill survey.

Here is that claim on your own job rather than in the abstract. These are the three occupations closest to this one by skill and subject matter — the places the work would most naturally transfer — with what the register scores them:

Industrial Machinery Mechanics SAFE 67/100 (+4) · 91% overlap
Engine and Other Machine Assemblers EXPOSED 34/100 (-29) · 90% overlap
Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic EXPOSED 35/100 (-28) · 89% overlap

That is the whole problem in three lines. The nearest work is not meaningfully safer, so there is no move here that trades a similar skill set for a better verdict. This is not us running out of ideas — it is what the neighbourhood looks like.

What would move this occupation up is the other direction, and on this page it's the more useful one.

What would move this back up — beyond any one person

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 78/100 — SAFE.

4 specific changes that would raise this score
  • already happening judgment accountability +4

    Insurer-driven condition-monitoring regimes (FM Global, Zurich equipment-breakdown coverage) that make the maintenance tech the person of record who accepts or overrides an AI vibration/thermography alarm and authorizes continued run. Once the model recommends and a human must accept residual risk in writing to keep coverage, the consequential call is formally owned. Already visible in refinery and utility reliability programs.

  • already happening task resistance +2

    Task-mix shift as CMMS/AI absorbs the routine tier — PM scheduling, manual lookup, parts sourcing, failure write-ups. The residual job is undocumented-fault diagnosis on aging non-instrumented machines, retrofit fabrication, and commissioning judgment. This occupation genuinely has two tiers, and the surviving tier is the harder one; watch for headcount falling while remaining roles are retitled 'reliability technician'.

  • plausible liability shield +6

    Extension of an existing named-individual certification regime to general machinery maintenance: OSHA Process Safety Management (29 CFR 1910.119) mechanical-integrity inspections already require documented qualified-person sign-off on covered process equipment, and ammonia refrigeration operators are pushed toward RETA CIRO/CARO credentials by insurers. If PSM-style mechanical integrity documentation, or a state boiler/pressure-vessel-style certificate of competency, were required for maintenance sign-off on guarded or energy-hazard machinery (LOTO release-to-service under 1910.147), the signature becomes a named licensed human rather than any available tech.

  • plausible trust premium +3

    OEM warranty and equipment-financing terms that void coverage unless service is performed by a factory-certified named technician (already standard in packaging, CNC, and medical-device manufacturing equipment). This is a plant-buyer preference for a specific credentialed human, not a general public trust premium, so the ceiling is low.

The limit. No realistic route to a consumer-style trust premium: buyers are plants purchasing uptime, and they will accept whatever mix of robot and human delivers it cheapest. Embodiment is already near maximum and cannot rise; it can only be eroded by cheaper general-purpose manipulators. The structural weakness — no licensure and no client relationship — is only fixable through safety-code or insurer mechanisms, and those attach to hazardous process equipment, not to machinery maintenance generally.

These are conditions, not forecasts — what would have to happen, not what will. Specific rules, cases and bills are named so you can go and check whether they exist and where they stand; verify before relying on any of them. Nothing here is legal or financial advice.

Where this work is, and what it pays there

BLS metro figures for 198 areas. The verdict above does not change by city — the rubric judges what the work involves, not where it happens — but pay and headcount do, and the national median hides a very wide range.

Most of these jobs

Dallas-Fort Worth-Arlington, TX 2,460 $60,770 +0%
Houston-Pasadena-The Woodlands, TX 1,950 $58,310 -4%
Atlanta-Sandy Springs-Roswell, GA 1,530 $56,340 -7%
Los Angeles-Long Beach-Anaheim, CA 1,310 $72,750 +20%
Orlando-Kissimmee-Sanford, FL 1,260 $48,270 -21%
New York-Newark-Jersey City, NY-NJ 1,170 $68,990 +13%
Baltimore-Columbia-Towson, MD 1,040 $59,570 -2%
Louisville/Jefferson County, KY-IN 970 $157,260 +158%

Best paid

Louisville/Jefferson County, KY-IN 970 $157,260 +158%
Beaumont-Port Arthur, TX 320 $91,440 +50%
Clarksville, TN-KY 70 $84,500 +39%

Percentages are against this occupation's national median of $60,850. Counts are jobs in that metro, not vacancies. Metros where the BLS suppressed the cell are absent rather than shown as zero.

Who is actually doing this — nobody, on the record

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 63. 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.

Read that as a gap in the reporting we can see, not proof of absence — the dispatch runs on English-language feeds and misses plenty. If you know of a case, tell us, or add a field report from inside the job.

Quick take — do you do this job?

Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

Field reports — what people say has changed

No field reports yet. A written account takes a paragraph rather than a tap, goes to an editor before it appears, and is the one thing on this page the rubric cannot produce on its own.

File a field report

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.

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