# Food and Tobacco Roasting, Baking, and Drying Machine Operators and Tenders

> Operate or tend food or tobacco roasting, baking, or drying equipment, including hearth ovens, kiln driers, roasters, char kilns, and vacuum drying equipment.

- **SOC code:** 51-3091.00
- **Canonical URL:** https://singulariki.com/roles/role-51-3091-00
- **Also known as:** Coffee Roaster, Machine Operator, Roaster, Roasterman, Bean Roaster, Line Operator, Oven Operator, Oven Technician
- **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):
- Observe, feel, taste, or otherwise examine products during and after processing to ensure conformance to standards.
- Take product samples during or after processing for laboratory analyses.
- Set temperature and time controls, light ovens, burners, driers, or roasters, and start equipment, such as conveyors, cylinders, blowers, driers, or pumps.
- Observe temperature, humidity, pressure gauges, and product samples and adjust controls, such as thermostats and valves, to maintain prescribed operating conditions for specific stages.
- Observe flow of materials and listen for machine malfunctions, such as jamming or spillage, and notify supervisors if corrective actions fail.
- Test products for moisture content, using moisture meters.
- Record production data, such as weight and amount of product processed, type of product, and time and temperature of processing.
- Weigh or measure products, using scale hoppers or scale conveyors.
- Clear or dislodge blockages in bins, screens, or other equipment, using poles, brushes, or mallets.
- Operate or tend equipment that roasts, bakes, dries, or cures food items such as cocoa and coffee beans, grains, nuts, and bakery products.
- Signal coworkers to synchronize flow of materials.
- Start conveyors to move roasted grain to cooling pans and agitate grain with rakes as blowers force air through perforated bottoms of pans.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Near Vision _(ability)_
- Operations Monitoring _(transferable_skill)_
- Production and Processing _(knowledge)_
- Monitoring _(essential_skill)_
- English Language _(knowledge)_
- Problem Sensitivity _(ability)_
- Reading Comprehension _(essential_skill)_
- Active Listening _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Operation and Control _(transferable_skill)_
- Quality Control Analysis _(transferable_skill)_
- Oral Comprehension _(ability)_

**Skills in demand:**
- English Language _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_
- Social Perceptiveness _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Finger Dexterity _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Writing _(Common Skill)_
- Visualization _(Specialized Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Email software

## AI exposure & outlook

- **AI task-overlap index:** 14th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 27th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 9th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 16th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 81st 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); 2.4k annual openings; 20.7k → 20.8k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $42,730; 19,500 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-51-3091-00_