Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Food Cooking Machine Operators and Tenders
Occupation · SOC 51-3093.00
Operate or tend cooking equipment, such as steam cooking vats, deep fry cookers, pressure cookers, kettles, and boilers, to prepare food products.
Also called: Fryer Operator · Kettle Fry Cook Operator · Machine Operator · Retort Operator · Cooker Operator · Food Production Worker · Mogul Operator · Oven Operator · Peeler Operator · Thermo Processor · Bakery Fryer · Blanching Machine Operator
Job family: Production Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-51-3093-00/context.md directly.
AI work map
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Market signal
Independent published positions, read together — not a forecast.
- About average employment outlook (+0.6% by 2034)
- 4,400 openings/yr
- Low AI exposure
- Median pay $40,550/yr
- Work is mostly on-site (not teleworkable)
- 2013 flagged this for computerization (52nd); today's AI task-overlap is comparatively low (24th)
24th-percentile task overlap — yet about 4,400 openings a year (+0.6% projected, BLS) . What exposure means →
AI & job outlook
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Exposure to current AI
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Low | 33rd | -0.6 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 17th | 0.1 | |
| AI assistant applicability (Microsoft) Low | 28th | 0.1 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.1), and including AI-powered software (γ 0.1). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
Historical automation estimate (2013)
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.6 · 52nd percentile among occupations · Moderate
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +0.6% by 2034 |
| Projected annual openings | 4,400 |
| Employment 2024 → 2034 | 29,700 → 29,900 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international 2 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Food Cooking Machine Operators and Tenders sits at the 18th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure rose from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
15% mean task exposure (2025)
18th percentile of 427 placed occupations
+2 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Food and Related Products Machine Operators · 8160 | 15% | Not exposed |
| Fruit, Vegetable and Related Preservers · 7514 | 15% | Not exposed |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
Tasks
All 17 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Clean, wash, and sterilize equipment and cooking area, using water hoses, cleaning or sterilizing solutions, or rinses. Core · importance 4.7
- Read work orders, recipes, or formulas to determine cooking times and temperatures, and ingredient specifications. Core · importance 4.6
- Observe gauges, dials, and product characteristics, and adjust controls to maintain appropriate temperature, pressure, and flow of ingredients. Core · importance 4.6
- Measure or weigh ingredients, using scales or measuring containers. Core · importance 4.5
- Tend or operate and control equipment, such as kettles, cookers, vats and tanks, and boilers, to cook ingredients or prepare products for further processing. Core · importance 4.5
- Record production and test data, such as processing steps, temperature and steam readings, cooking time, batches processed, and test results. Core · importance 4.5
- Set temperature, pressure, and time controls, and start conveyers, machines, or pumps. Core · importance 4.4
- Activate agitators and paddles to mix or stir ingredients, stopping machines when ingredients are thoroughly mixed. Supplemental · importance 4.4
- Remove cooked material or products from equipment. Core · importance 4.4
- Collect and examine product samples during production to test them for quality, color, content, consistency, viscosity, acidity, or specific gravity. Core · importance 4.3
- Operate auxiliary machines and equipment, such as grinders, canners, and molding presses, to prepare or further process products. Supplemental · importance 4.3
- Pour, dump, or load prescribed quantities of ingredients or products into cooking equipment, manually or using a hoist. Core · importance 4.3
- Listen for malfunction alarms, and shut down equipment and notify supervisors when necessary. Core · importance 4.3
- Notify or signal other workers to operate equipment or when processing is complete. Core · importance 4.2
- Place products on conveyors or carts, and monitor product flow. Supplemental · importance 4.2
- Turn valves or start pumps to add ingredients or drain products from equipment and to transfer products for storage, cooling, or further processing. Core · importance 4.2
- Admit required amounts of water, steam, cooking oils, or compressed air into equipment, such as by opening water valves to cool mixtures to the desired consistency. Core · importance 4.2
Work activities
- Record operational or production data.
- Watch operating equipment to detect malfunctions.
- Operate cooking, baking, or other food preparation equipment.
- Notify others of equipment repair or maintenance needs.
- Inspect food products.
- Collect samples of materials or products for testing.
- Monitor instruments to ensure proper production conditions.
- Adjust equipment controls to regulate flow of production materials or products.
- Read work orders or other instructions to determine product specifications or materials requirements.
- Review blueprints or other instructions to determine operational methods or sequences.
- Clean work areas.
- Sterilize food cooking or processing equipment.
- Adjust temperature controls of ovens or other heating equipment.
- Operate pumping systems or equipment.
- Measure ingredients or substances to be used in production processes.
- Adjust equipment controls to regulate coolant flow.
- Remove products or workpieces from production equipment.
- Signal others to coordinate work activities.
- Move products, materials, or equipment between work areas.
- Load materials into production equipment.
- Lift materials or workpieces using cranes or other lifting equipment.
- Operate mixing equipment.
- Operate grinding equipment.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Production and Processing | 4.3 | |
| Food Production | 3.8 | |
| Administration and Management | 3.3 | |
| Education and Training | 3.1 | |
| Mechanical | 3.1 | |
| English Language | 2.8 |
Abilities
| Problem Sensitivity | 3.6 | |
| Oral Comprehension | 3.4 | |
| Written Comprehension | 3.4 | |
| Near Vision | 3.3 | |
| Information Ordering | 3.1 | |
| Selective Attention | 3.1 | |
| Control Precision | 3.1 | |
| Arm-Hand Steadiness | 3.0 | |
| Manual Dexterity | 3.0 | |
| Finger Dexterity | 3.0 | |
| Reaction Time | 3.0 | |
| Oral Expression | 2.9 | |
| Deductive Reasoning | 2.9 | |
| Inductive Reasoning | 2.9 | |
| Speech Recognition | 2.9 | |
| Speech Clarity | 2.9 | |
| Written Expression | 2.8 | |
| Category Flexibility | 2.8 | |
| Perceptual Speed | 2.8 | |
| Multilimb Coordination | 2.8 | |
| Rate Control | 2.8 | |
| Static Strength | 2.8 | |
| Hearing Sensitivity | 2.8 |
Transferable skills
| Operations Monitoring | 3.5 | |
| Operation and Control | 3.1 | |
| Coordination | 2.9 | |
| Complex Problem Solving | 2.9 | |
| Quality Control Analysis | 2.8 | |
| Judgment and Decision Making | 2.8 |
Essential skills
| Reading Comprehension | 3.1 | |
| Monitoring | 3.1 | |
| Active Listening | 3.0 | |
| Critical Thinking | 3.0 | |
| Writing | 2.8 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Tools & technology
| Example | Category | |
|---|---|---|
| Database software | Data base user interface and query software |
Work context
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
How to get in
- Job zone
- Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
- Education
- Usually requires a high school diploma or GED, though some occupations may not.
- Typical entry-level education
- High school diploma or equivalent · BLS, the typical path — not a requirement
- Related experience
- Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
- Preparation level
- SVP (Below 6.0) — total schooling plus on-the-job experience.
Education of current workers
Share of people in this occupation at each level of education.
| High School Diploma | 85.9% | |
| Post-Secondary Certificate | 14.0% | |
| Less than a High School Diploma | 0.1% | |
| Some College Courses | 0.1% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 6.8 | |
| Conventional | 4.7 | |
| Investigative | 2.0 | |
| Enterprising | 1.7 | |
| Social | 1.3 |
Interest areas
| Physical/Manual Labor | 3.6 | |
| Mechanics/Electronics | 3.0 | |
| Culinary Art | 2.3 | |
| Transportation/Machine Operation | 2.0 | |
| Engineering | 1.8 | |
| Agriculture | 1.4 | |
| Physical Science | 1.3 | |
| Mathematics/Statistics | 1.3 |
Work styles
| Dependability | 2.1 | |
| Attention to Detail | 2.0 | |
| Cautiousness | 1.8 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $30,540 |
| 25th percentile | $35,310 |
| Median (50th) | $40,550 |
| 75th percentile | $47,420 |
| 90th percentile | $54,170 |
| People employed | 27,660 |
Industries that employ this occupation
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Manufacturing · Sector | 22,480 | $42,080 |
| Accommodation and Food Services · Sector | 1,990 | $39,670 |
| Wholesale Trade · Sector | 1,620 | $33,570 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 640 | $36,120 |
| Temporary Help Services · National industry | 640 | $35,780 |
| Retail Trade · Sector | 580 | $31,470 |
| Transportation and Warehousing · Sector | 310 | $35,080 |
| Full-Service Restaurants · National industry | — | $34,590 |
Where this work is most concentrated
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Manufacturing · Sector | 9.82× | 22,480 |
| Wholesale Trade · Sector | 1.5× | 1,620 |
| Temporary Help Services · National industry | 1.35× | 640 |
| Accommodation and Food Services · Sector | 0.78× | 1,990 |
| Administrative and Support and Waste Management and Remediation Services · Sector | 0.4× | 640 |
| Transportation and Warehousing · Sector | 0.23× | 310 |
| Retail Trade · Sector | 0.21× | 580 |
Related occupations
Part of the Advanced Manufacturing career cluster.
- Food Batchmakers · 51-3092.00 Compare →
- Food and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders · 51-3091.00 Compare →
- Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders · 51-9012.00 Compare →
- Cooling and Freezing Equipment Operators and Tenders · 51-9193.00 Compare →
- Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders · 51-9192.00 Compare →
- Bakers · 51-3011.00 Compare →
- Mixing and Blending Machine Setters, Operators, and Tenders · 51-9023.00 Compare →
- Furnace, Kiln, Oven, Drier, and Kettle Operators and Tenders · 51-9051.00 Compare →
- Packaging and Filling Machine Operators and Tenders · 51-9111.00 Compare →
- Cooks, Restaurant · 35-2014.00 Compare →
- Graders and Sorters, Agricultural Products · 45-2041.00 Compare →
- Extruding, Forming, Pressing, and Compacting Machine Setters, Operators, and Tenders · 51-9041.00 Compare →
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
What you can do with this
Options the data surfaces for Food Cooking Machine Operators and Tenders — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Skills that travel
Capabilities this work builds that are used across many other occupations.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
- Food Batchmakers Compare →
- Food and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders Compare →
- Separating, Filtering, Clarifying, Precipitating, and Still Machine Setters, Operators, and Tenders Compare →
- Cooling and Freezing Equipment Operators and Tenders Compare →
- Cleaning, Washing, and Metal Pickling Equipment Operators and Tenders Compare →
Paths in
How people typically prepare for this work.
- High school diploma or equivalent · typical entry level
- Job zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed · preparation tier
Zoom out
On the global GenAI exposure gradient this work sits around the 18th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Food Cooking Machine Operators and Tenders show 24th-percentile AI task overlap — and about 4,400 annual U.S. openings
- Food Cooking Machine Operators and Tenders rank in the 24th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
- The occupation is projected to see about 4,400 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
- BLS projects employment to be about average (+0.6%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $40,550, across about 27,660 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Food Cooking Machine Operators and Tenders show 24th-percentile AI task overlap — and about 4,400 annual U.S. openings • Food Cooking Machine Operators and Tenders rank in the 24th percentile (Low band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 4,400 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be about average (+0.6%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $40,550, across about 27,660 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Food Cooking Machine Operators and Tenders". https://singulariki.com/roles/role-51-3093-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Food Cooking Machine Operators and Tenders." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-51-3093-00
APA
Singulariki. (2026). Food Cooking Machine Operators and Tenders. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-51-3093-00
BibTeX
@misc{singulariki-role-51-3093-00,
title = {Food Cooking Machine Operators and Tenders},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-51-3093-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.