← Risk register SOC 51-2031 · reviewed 2026-08-11

Engine and Other Machine Assemblers

34,000 US workers · median $53,710/yr · Production

EXPOSED

Fitting crankshafts, torquing head bolts, aligning gears and verifying tolerances is hand work, not screen work, so language AI barely touches the core day. The real pressure is industrial robotics and fixture automation, which already own high-volume engine lines — what survives is low-volume, large, or variant-heavy builds (marine, industrial, rebuilds, prototypes) where tooling up a cell costs more than a skilled assembler. No license, no client relationship, and work instructions define most decisions, so the only moats are hands and physical presence.

10-year outlook: High-volume engine assembly headcount keeps thinning as lines automate, while custom, industrial, and rebuild assembly holds — expect fewer jobs and a skill shift toward troubleshooting and machine tending.

US employment, 2019–2025-26.1%
45,98034,000 workers

Part 2020 shock, part continued decline in the years since.

Median pay $45,660 → $53,710 -5.9% in real terms (nominal +17.6%, 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

-21.1% 38,400 → 30,300 on the projections basis

Exposed, and shrinking

Both signals point the same way: the tasks are largely automatable and the BLS projects -21.1% by 2034. This is the case where the score and the forecast agree, and it is the one worth taking seriously.

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.

~2,800 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.

FitterAssemblerValve MakerMotor SetterSubassemblerValve SetterEngine BuilderCell TechnicianCrane AssemblerMachine BuilderMotor InstallerEngine AssemblerMotors AssemblerAssembler ErectorMachine AssemblerProduct AssemblerTurbine AssemblerInjector AssemblerGenerator AssemblerRace Engine BuilderAssembly Line WorkerCompressor AssemblerJet Engine AssemblerMechanical Assembler

Score — 34/100 resistance

Holding it up: task resistance (13/20). Weakest point: liability shield (2/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 13 + 11 + 2 + 3 + 5 = 34. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 13/20

Mixed — a routine tier and a judgment tier At 13 the score credits what a robot cell still can't do cheaply — feeling a bearing preload, chasing an interference fit on a rebuilt block, working from a marked-up print on a one-off marine or genset build — but it stops short of 14+ because the repetitive torque sequences, gasket placement and press-fit operations that fill a high-volume shift are already done by fixture automation and torque robots on the big lines.

Embodiment 11/20

Some physical or field component An 11 reflects that you're standing at a bench or line with air tools, hoists, presses and micrometers on physical parts — real force, real reach, real dexterity — but the environment is a controlled indoor plant floor with fixed stations, part kitting and defined lighting, not the unpredictable field conditions of a millwright crawling inside a running facility.

Liability shield 2/20

No licence, no signature requirement A 2 is because nothing you install requires you to hold a license or sign off in your own name; the plant's quality inspector, the engineering spec and the manufacturer's warranty absorb the consequence of a bad build, and your traceability stamp on a work order is a shop record, not personal legal exposure.

Trust premium 3/20

Anonymous artifact production A 3 acknowledges only that a foreman knows which assembler to hand the difficult rebuild to — the customer who buys the engine never learns your name, and the assembly can be transferred to another plant or another worker without a single conversation being lost.

Judgment & accountability 5/20

Executes defined procedures on defined inputs At 5, most calls are already made for you by the build sheet, torque spec and go/no-go gauge; the discretion that keeps this above the floor is the decision to stop the line, tag a part out of tolerance, or flag a fit problem before it becomes scrap — real judgment, but exercised inside documented procedure rather than owning the outcome.

Scored twice. An independent second run returned 36/100 — EXPOSED, agreeing with the verdict above.

This score sits on a verdict boundary. At 34/100 it is one point from COOKED. Re-scoring moves results by a point or two, so here the score is more informative than the label.

Confidence: medium · 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, physical-presence

How to future-proof this job

Training paths for your skill gaps: Coursera — customer service and client-facing skill courses free to audit · MIT OpenCourseWare — full course materials across every department, free free · Coursera — engineering and procurement courses, auditable without paying free to audit · Apprenticeship.gov — paid, employer-sponsored trade apprenticeships, searchable by trade and ZIP paid to train · Apprenticeship.gov — industrial maintenance and millwright programs paid to train · Apprenticeship.gov — electrical, HVAC, plumbing and fitting programs that pay while you learn paid to train

All 35 skills ranked by how many jobs they open →

Where this experience transfers — occupations you could move toward

Computed from U.S. Dept. of Labor O*NET skill and knowledge profiles: high overlap with what you already do, a materially higher resistance score, no large jump in required training, and no licence you would have to start a new pipeline to get. Targets that pay meaningfully less, that are themselves COOKED, or whose own headcount is falling are excluded — a move into a shrinking trade is not an escape.

Automotive Body and Related Repairers EXPOSED · 65/100 · you already have ~88% of the skill profile

Skills to close: Service Orientation, Active Learning

Electric Motor, Power Tool, and Related Repairers EXPOSED · 60/100 · you already have ~84% of the skill profile

Skills to close: Equipment Selection, Repairing, Equipment Maintenance, Installation

Refractory Materials Repairers, Except Brickmasons EXPOSED · 65/100 · you already have ~83% of the skill profile

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 49/100, still EXPOSED.

4 specific changes that would raise this score
  • already happening task resistance +3

    Task-mix shift as high-volume cells finish automating: what remains is prototype/first-article builds, rebuild teardown where wear diagnosis and reuse/scrap calls are unstructured, and variant-heavy marine/industrial engines where BOMs and fits change per unit. This tier resists both robotics and instruction-following AI because the build sequence is not stable enough to fixture.

  • plausible embodiment +4

    Concentration into large-displacement and field work — locomotive, marine, stationary gensets, wind gearbox rebuilds — where the machine cannot be brought to a cell and assembly happens in situ with confined-space and overhead access. Field-service engine assembly is already a distinct pay tier at EMD/Caterpillar dealers.

  • plausible judgment accountability +4

    If insurers or OEM warranty programs require a named assembler-of-record accountable for torque-sequence and clearance decisions on critical rotating assemblies — the way turbine and nuclear pump rebuilds already carry traveler sign-off per build step — the role owns consequential calls rather than executing instructions.

  • unlikely liability shield +4

    Airworthiness-style sign-off spreading beyond aviation: FAA Part 65 A&P certification already makes a named licensed human personally responsible for engine assembly and return-to-service. An analogous mandatory stamped sign-off in marine propulsion (USCG/ABS surveyor-witnessed assembly of critical rotating assemblies) or in EPA/CARB emissions-critical rebuild certification would attach a named human to the torque record.

The limit. Even with every lever, this stays a mid-scoring occupation: the headcount trend is set by robotics capex in high-volume plants, not by any of these moats. Trust premium has no realistic route — buyers purchase an engine, not an assembler, and no end customer knows or pays for who built it.

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 41 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

Detroit-Warren-Dearborn, MI 3,330 $64,820 +21%
Greenville-Anderson-Greer, SC 1,020 $46,950 -13%
Los Angeles-Long Beach-Anaheim, CA 660 $46,620 -13%
Chicago-Naperville-Elgin, IL-IN 540 $49,630 -8%
Grand Rapids-Wyoming-Kentwood, MI 460 $53,570 +0%
Virginia Beach-Chesapeake-Norfolk, VA-NC 360 $36,030 -33%
Boston-Cambridge-Newton, MA-NH 310 $48,990 -9%
Toledo, OH 310 $75,770 +41%

Best paid

Seattle-Tacoma-Bellevue, WA 210 $102,530 +91%
Indianapolis-Carmel-Greenwood, IN 200 $80,200 +49%
Oshkosh-Neenah, WI 90 $80,170 +49%

Percentages are against this occupation's national median of $53,710. 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 34. 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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Kept current

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