# Cooling and Freezing Equipment Operators and Tenders

> Operate or tend equipment such as cooling and freezing units, refrigerators, batch freezers, and freezing tunnels, to cool or freeze products, food, blood plasma, and chemicals.

- **SOC code:** 51-9193.00
- **Canonical URL:** https://singulariki.com/roles/role-51-9193-00
- **Also known as:** Freezer Operator, Freezer Person, Refrigeration Operator, Refrigeration Technician, Certified Refrigeration Operator, Compressor Operator, Engine Room Operator, Ice Cream Maker
- **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):
- Record temperatures, amounts of materials processed, or test results on report forms.
- Monitor pressure gauges, ammeters, flowmeters, thermometers, or products, and adjust controls to maintain specified conditions, such as feed rate, product consistency, temperature, air pressure, and machine speed.
- Read dials and gauges on panel control boards to ascertain temperatures, alkalinities, and densities of mixtures, and turn valves to obtain specified mixtures.
- Measure or weigh specified amounts of ingredients or materials, and load them into tanks, vats, hoppers, or other equipment.
- Adjust machine or freezer speed and air intake to obtain desired consistency and amount of product.
- Start machinery, such as pumps, feeders, or conveyors, and turn valves to heat, admit, or transfer products, refrigerants, or mixes.
- Weigh packages and adjust freezer air valves or switches on filler heads to obtain specified amounts of product in each container.
- Correct machinery malfunctions by performing actions such as removing jams, and inform supervisors of malfunctions as necessary.
- Inspect and flush lines with solutions or steam, and spray equipment with sterilizing solutions.
- Load and position wrapping paper, sticks, bags, or cartons into dispensing machines.
- Sample and test product characteristics such as specific gravity, acidity, and sugar content, using hydrometers, pH meters, or refractometers.
- Start agitators to blend contents, or start beater, scraper, and expeller blades to mix contents with air and prevent sticking.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Operations Monitoring _(transferable_skill)_
- Production and Processing _(knowledge)_
- Operation and Control _(transferable_skill)_
- Near Vision _(ability)_
- Critical Thinking _(essential_skill)_
- Problem Sensitivity _(ability)_
- Monitoring _(essential_skill)_
- Complex Problem Solving _(transferable_skill)_
- Deductive Reasoning _(ability)_
- Mechanical _(knowledge)_
- English Language _(knowledge)_
- Food Production _(knowledge)_

**Skills in demand:**
- Critical Thinking _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- English Language _(Common Skill)_
- Finger Dexterity _(Common Skill)_
- Equipment Maintenance _(Specialized Skill)_
- Mathematics _(Common Skill)_
- Time Management _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft PowerPoint _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_
- Google Gmail

## AI exposure & outlook

- **AI task-overlap index:** 18th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 19th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 11th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 33rd percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 84th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 7.2% growth (Growing fast); 0.8k annual openings; 7.1k → 7.6k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $40,160; 6,590 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-51-9193-00_