# Food Cooking Machine Operators and Tenders

> Operate or tend cooking equipment, such as steam cooking vats, deep fry cookers, pressure cookers, kettles, and boilers, to prepare food products.

- **SOC code:** 51-3093.00
- **Canonical URL:** https://singulariki.com/roles/role-51-3093-00
- **Also known as:** Fryer Operator, Kettle Fry Cook Operator, Machine Operator, Retort Operator, Cooker Operator, Food Production Worker, Mogul Operator, Oven Operator
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Clean, wash, and sterilize equipment and cooking area, using water hoses, cleaning or sterilizing solutions, or rinses.
- Read work orders, recipes, or formulas to determine cooking times and temperatures, and ingredient specifications.
- Observe gauges, dials, and product characteristics, and adjust controls to maintain appropriate temperature, pressure, and flow of ingredients.
- Measure or weigh ingredients, using scales or measuring containers.
- Tend or operate and control equipment, such as kettles, cookers, vats and tanks, and boilers, to cook ingredients or prepare products for further processing.
- Record production and test data, such as processing steps, temperature and steam readings, cooking time, batches processed, and test results.
- Set temperature, pressure, and time controls, and start conveyers, machines, or pumps.
- Activate agitators and paddles to mix or stir ingredients, stopping machines when ingredients are thoroughly mixed.
- Remove cooked material or products from equipment.
- Collect and examine product samples during production to test them for quality, color, content, consistency, viscosity, acidity, or specific gravity.
- Operate auxiliary machines and equipment, such as grinders, canners, and molding presses, to prepare or further process products.
- Pour, dump, or load prescribed quantities of ingredients or products into cooking equipment, manually or using a hoist.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Production and Processing _(knowledge)_
- Food Production _(knowledge)_
- Problem Sensitivity _(ability)_
- Operations Monitoring _(transferable_skill)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Administration and Management _(knowledge)_
- Near Vision _(ability)_
- Education and Training _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Monitoring _(essential_skill)_
- Operation and Control _(transferable_skill)_

**Skills in demand:**
- Reading Comprehension _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Finger Dexterity _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- English Language _(Common Skill)_
- Writing _(Common Skill)_
- Time Management _(Common Skill)_

**Tools & technology:**
- Database software

## AI exposure & outlook

- **AI task-overlap index:** 24th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 33rd percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 17th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 28th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 52nd percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 0.6% growth (About average); 4.4k annual openings; 29.7k → 29.9k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $40,550; 27,660 employed.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-51-3093-00_