# Model Makers, Metal and Plastic

> Set up and operate machines, such as lathes, milling and engraving machines, and jig borers to make working models of metal or plastic objects. Includes template makers.

- **SOC code:** 51-4061.00
- **Canonical URL:** https://singulariki.com/roles/role-51-4061-00
- **Also known as:** CNC Machinist (Computer Numerical Control Machinist), Model Builder, Model Maker, Molding Technician (Molding Tech), CNC Programmer (Computer Numerical Control Programmer), Metal Model Maker, Model Maker Machinist, Model Technician (Model Tech)
- **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):
- Study blueprints, drawings, and sketches to determine material dimensions, required equipment, and operations sequences.
- Set up and operate machines, such as lathes, drill presses, punch presses, or bandsaws, to fabricate prototypes or models.
- Program computer numerical control (CNC) machines to fabricate model parts.
- Inspect and test products to verify conformance to specifications, using precision measuring instruments or circuit testers.
- Cut, shape, and form metal parts, using lathes, power saws, snips, power brakes and shears, files, and mallets.
- Rework or alter component model or parts as required to ensure that products meet standards.
- Drill, countersink, and ream holes in parts and assemblies for bolts, screws, and other fasteners, using power tools.
- Grind, file, and sand parts to finished dimensions.
- Devise and construct tools, dies, molds, jigs, and fixtures, or modify existing tools and equipment.
- Record specifications, production operations, and final dimensions of models for use in establishing operating standards and procedures.
- Align, fit, and join parts, using bolts and screws or by welding or gluing.
- Use computer-aided design (CAD) and computer-aided manufacturing (CAM) software or hardware to fabricate model parts.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mechanical _(knowledge)_
- Mathematics _(knowledge)_
- Near Vision _(ability)_
- Production and Processing _(knowledge)_
- Design _(knowledge)_
- Engineering and Technology _(knowledge)_
- Visualization _(ability)_
- Operation and Control _(transferable_skill)_
- Arm-Hand Steadiness _(ability)_
- Manual Dexterity _(ability)_
- Finger Dexterity _(ability)_
- Control Precision _(ability)_

**Skills in demand:**
- Mathematics _(Common Skill)_
- Visualization _(Specialized Skill)_
- Finger Dexterity _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Time Management _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Equipment Selection _(Specialized Skill)_
- Speech Recognition _(Specialized Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Word _(hot technology)_
- CNC Software Mastercam
- PTC Creo Parametric

## AI exposure & outlook

- **AI task-overlap index:** 21st 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):** 24th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 17th 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):** -18.2% growth (Declining); 0.3k annual openings; 3.2k → 2.6k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $62,700; 3,230 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-51-4061-00_