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Plant and machine operators, and assemblers · code 8160

Food and related products machine operators

Food and related products machine operators set, operate and attend machinery used to slaughter animals and trim meat from carcasses; bake, freeze, heat, crush, mix, blend and otherwise process foodstuffs, beverages and tobacco leaves. Tasks include - (a) operating and monitoring machinery used to restrain, stun and slaughter animals and to trim carcasses into standard meat and fish cuts; (b) setting, operating and attending machinery and ovens to mix, bake and otherwise prepare bread and flour confectionery products; (c) operating machinery to crush, mix, malt, cook and ferment grains and fruits to produce beer, wines, malt liquors, vinegar, yeast and related products; (d) attending equipment to make jam, toffee, cheese, processed cheese, margarine, syrup, ice, pasta, ice-cream, sausages, chocolate, maize starch, edible fats and dextrin; (e) operating equipment to cool, heat, dry, roast, blanch, pasteurize, smoke, sterilize, freeze, evaporate and concentrate foodstuffs and liquids used in food processing; (f) mixing, pulping, grinding, blending and separating foodstuffs and liquids with churning, pressing, sieving, grinding and filtering equipment; (g) processing tobacco leaves by machine to make cigarettes, cigars, pipe and other tobacco products. Examples of the occupations classified here: - Bakery products machine operator - Bread production machine operator - Chocolate production machine operator - Cigarette production machine operator - Cigar production machine operator - Dairy products machine operator - Fish processing machine operator - Meat processing machine operator - Milk processing machine operator Some related occupations classified elsewhere: - Bottling machine operator - 8183

None of this job's tasks scored high enough to count. It ranks 78 of 427 for holding up against AI.

Also known as

  • flour purifier operator
  • refining machine operator
  • cigarette making machine operator
  • vermouth manufacturer
  • cacao bean roaster
  • distillery worker
  • chilling operator
  • food production operator
  • malt kiln operator
  • chocolate moulding operator
  • dairy products manufacturing worker
  • fish canning operator
  • distillery miller
  • extract mixer tester
  • bulk filler
  • sauce production operator
  • honey extractor
  • blanching operator
  • liquor blender
  • yeast distiller
  • fruit and vegetable canner
  • prepared meat operator
  • cellar operator
  • blending plant operator
  • fat-purification worker
  • liquor grinding mill operator
  • beverage filtration technician
  • brew house operator
  • candy machine operator
  • blender operator
  • dairy processing operator
  • milk heat treatment process operator
  • miller
  • starch extraction operator
  • coffee roaster
  • kettle tender
  • cocoa mill operator
  • pasta operator
  • fruit-press operator
  • starch converting operator
  • centrifuge operator
  • sugar refinery operator
  • baking operator
  • cocoa press operator
  • clarifier
  • animal feed operator
  • hydrogenation machine operator
  • cider fermentation operator
  • cacao beans cleaner
  • germination operator
  • coffee grinder
  • carbonation operator
  • wine fermenter
  • dryer attendant
  • fish production operator

Job titles from the EU's ESCO list. Search for any of them on the jobs page and you'll end up here.

84.7
Holds up
against AI Not Exposed

AI could take on 15.3 of 100, on average
so it holds up at 100 − 15.3 = 84.7

That's the whole sum, and you can check it against the ILO's study.

66.9
How hands-on
out of 100

From O*NET, averaged across 5 US jobs

36.8
How fiddly
and cramped

finger skill 39.3 · hand skill 41.8 · cramped spaces 29.2 · averaged

Kind of hands-on work · hands-on 50+ · fiddly under 39.4 Hands-on, less fiddly work

Less fine handwork and fewer cramped spaces than a typical hands-on job. That clears one hurdle for machines. It doesn't mean machines are doing this work yet.

estimated O*NET 31.0 BLS occupational crosswalk chain ISCO-08 to 2010 SOC (Aug 2012, rev. Jun 2015); 2010 to 2018 SOC (Nov 2017); O*NET-SOC 2019 taxonomy data 0.7-work-setting measures chosen by Frey & Osborne (2017) · the grouping is a sorting, not a measurement

This number is probably too high

This score only looks at AI tools like chatbots. It doesn't look at robots at all — and this job rates 66.9 out of 100 for how hands-on it is, which is exactly where robots come in.

Have a look at the tasks below and judge for yourself. The ILO scored them low because a chatbot can't do them. Whether a machine with hands could is a different question, and we can't answer it yet.

The tasks behind the score

The score is the average of these. A job is really a bundle of tasks, and an average can hide how uneven that bundle is.

The task AI could do most of scores 19, while the average is 15.3. A big gap means some of this job is wide open to AI and some of it barely at all. That's quite different from a job where everything sits somewhere in the middle, even when the averages match.

  1. 19

    Mixing, pulping, grinding, blending and separating foodstuffs and liquids with churning, pressing, sieving, grinding and filtering equipment

    Very Low
  2. 17.7

    Attending equipment to make jam, toffee, cheese, processed cheese, margarine, syrup, ice, pasta, ice-cream, sausages, chocolate, maize starch, edible fats and dextrin

    Very Low
  3. 17.5

    Operating equipment to cool, heat, dry, roast, blanch, pasteurize, smoke, sterilize, freeze, evaporate and concentrate foodstuffs and liquids used in food processing

    Very Low
  4. 15.5

    Setting, operating and attending machinery and ovens to mix, bake and otherwise prepare bread and flour confectionery products

    Very Low
  5. 13.5

    Processing tobacco leaves by machine to make cigarettes, cigars, pipe and other tobacco products.

    Very Low
  6. 13.1

    Operating machinery to crush, mix, malt, cook and ferment grains and fruits to produce beer, wines, malt liquors, vinegar, yeast and related products

    Very Low
  7. 11

    Operating and monitoring machinery used to restrain, stun, slaughter animals and to trim carcasses into standard meat and fish cuts

    Very Low

7 tasks · the High to Very Low labels are the ILO's

from the source Working Paper 140, Generative AI and Jobs 2025 index data 0.7-work-setting

Helped, or replaced?

The score above can't tell a tool that makes you faster from one that does the task instead of you. Jobs and Skills Australia looked at those two things separately, and this is their result, matched to this job.

3 Australian jobs match this one, and we've simply averaged them. Treat the numbers as a rough guide.

AI helps you
49.3
AI does it for you
22.3

Helping wins by 27 points.

estimated Our Gen AI Transition (Gen AI Capacity Study) September 2025 detailed data release data 0.7-work-setting matched to Australian jobs 7129, 8311, 8313

Compared with similar jobs

There are 39 jobs in the “Plant and machine operators, and assemblers” group, averaging 80. This one is above that.