COOKED
The core loop — feed materials, monitor fill weights and seals, log counts, clear jams, run changeovers — sits inside a controlled, repeatable factory environment, which is exactly where conventional automation and machine vision already win; AI mainly accelerates the inspection and scheduling layers that used to justify a human tender. Physical presence still matters for jam clearing, tooling changeovers, sanitation and material handling, which is why the job doesn't vanish overnight, but headcount per line keeps falling as vision-based QC and auto-changeover systems get cheaper. No license, no client relationship, and almost no discretionary authority to fall back on.
Roughly flat across the period, with year-to-year wobble.
Median pay $30,990 → $43,220 +11.6% 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
+4.5% 381,200 → 398,200 on the projections basis
Exposed, but growing
AI can already do a lot of these tasks, and the BLS still expects +4.5% more of these jobs by 2034. Demand for the output is growing faster than the work is being automated away — the mechanism BLS gives for software developers, and the combination people most often misread as an error.
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.
~45,300 openings a year on average, including replacing people who leave.
BalerBanderCannerCapperCarderCorkerFillerNesterSealerBlockerBottlerBundlerLabelerStufferOperatorPackagerCan CapperCan FillerCan SealerJar CapperJar FillerKeg FillerKeg HeaderPalletizer
Holding it up: embodiment . Weakest point: trust premium .
Mixed — a routine tier and a judgment tier Checkweighers, vision seal inspection and PLC recipe recall already cover the monitored steps, and the counting and downtime logging that used to be your clipboard now writes itself into the MES — what keeps this at 8 rather than 3 is that a bag jam in a VFFS former, a film splice, or swapping change parts for a different bottle diameter still needs hands and feel that no line has bought out yet.
Hands-on in uncontrolled environments You are on the floor for a full shift: reaching into guarded machine sections after lockout to pull crushed cartons, wet-sanitation washdown on food lines, lifting film reels and cases, standing on concrete near moving conveyors — 13 not higher because it is your plant, your fixed line, with known layout and controlled temperature, not a construction site or a customer's roof.
No licence, no signature requirement There is no operator license for a filler; a forklift cert or food-handler card and internal SOP sign-offs are the ceiling, and when a lot ships underweight or with a bad seal it is the QA manager and the plant's HACCP or FDA-registered facility responsibility on the line, not your name — hence 2 rather than 0, since documented GMP training does exist.
Executes defined procedures on defined inputs Your calls are bounded ones — stop the line, adjust a fill target within tolerance, tag out a bad head, call maintenance — all with a defined trigger and a spec sheet behind them, and the 4 reflects that you decide when to pull the andon and quarantine product rather than being a pure button-pusher.
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 (8/20 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 (2/20) is whether the law requires a licensed human to sign. Trust premium (2/20) is whether buyers specifically pay for a person. Judgment and accountability (4/20) 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 8 of this occupation's 29 points (28%).
Embodiment (13/20) 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.
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 41/100 — EXPOSED.
Genuine two-tier structure: once vision QC and auto-changeover absorb monitoring and logging, what remains is unscripted — novel jam root-causing, seal-failure diagnosis across film lots, sanitation validation, and tooling fit on short-run SKUs. If SKU proliferation and contract-packaging short runs continue (already visible in co-packer growth), changeovers per shift rise and the residual job is the diagnostic tier.
FDA's FSMA Preventive Controls rule (21 CFR 117) already requires a trained 'preventive controls qualified individual' to verify and sign CCP monitoring records; if FDA or a customer-driven scheme (SQF/BRCGS) tightened this so the line operator personally signs each fill-weight/seal-integrity CCP verification rather than a plant QA manager signing in aggregate — or if the DSCSA/compounded-drug fill side extended named-operator batch-record signing to consumer packaging — a signature duty attaches to the tender role. Similar for NIST Handbook 133 net-content checks under state weights-and-measures inspection.
If recall-driven audits push plants to give the line tender documented stop-line authority (an Andon/stop-ship call that cannot be overridden by scheduling), as some UFCW and Teamsters food-plant contracts and post-recall consent decrees have formalized, the role owns a consequential ambiguous call — hold or release a suspect lot.
Aseptic and allergen-segregated lines, plus cannabis/nutraceutical fill rooms with heavy sanitation and manual clean-in-place teardown, keep hands inside the machine; if allergen cross-contact rules or state cannabis packaging rules mandate documented manual teardown between runs, physical presence per line increases.
The limit. No realistic trust-premium route — buyers never see or select the operator, and the output is a sealed anonymous package. Even with every lever, this stays a headcount-per-line story: total employment falls as vision QC and auto-changeover spread, regardless of what the remaining role is allowed to sign.
| Chicago-Naperville-Elgin, IL-IN | 21,830 | $43,290 +0% |
| New York-Newark-Jersey City, NY-NJ | 16,110 | $38,790 -10% |
| Los Angeles-Long Beach-Anaheim, CA | 13,990 | $43,470 +1% |
| Dallas-Fort Worth-Arlington, TX | 8,240 | $40,610 -6% |
| Phoenix-Mesa-Chandler, AZ | 6,100 | $42,450 -2% |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 5,770 | $44,340 +3% |
| St. Louis, MO-IL | 4,910 | $47,460 +10% |
| Cincinnati, OH-KY-IN | 4,770 | $45,570 +5% |
| Fort Collins-Loveland, CO | 670 | $79,800 +85% |
| Salisbury, MD | 60 | $69,060 +60% |
| Cedar Rapids, IA | 1,080 | $67,700 +57% |
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 29. 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.