# Tool and Die Makers

> Analyze specifications, lay out metal stock, set up and operate machine tools, and fit and assemble parts to make and repair dies, cutting tools, jigs, fixtures, gauges, and machinists' hand tools.

- **SOC code:** 51-4111.00
- **Canonical URL:** https://singulariki.com/roles/role-51-4111-00
- **Also known as:** Tool Maker, Tool and Die Machinist, Tool and Die Maker, Tool and Fixture Specialist, Die Machinist, Die Repair Laborer, Die Repair Technician (Die Repair Tech), Jig and Fixture Repairer
- **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):
- Verify dimensions, alignments, and clearances of finished parts for conformance to specifications, using measuring instruments such as calipers, gauge blocks, micrometers, or dial indicators.
- Set up and operate conventional or computer numerically controlled machine tools such as lathes, milling machines, or grinders to cut, bore, grind, or otherwise shape parts to prescribed dimensions and finishes.
- Visualize and compute dimensions, sizes, shapes, and tolerances of assemblies, based on specifications.
- Study blueprints, sketches, models, or specifications to plan sequences of operations for fabricating tools, dies, or assemblies.
- Fit and assemble parts to make, repair, or modify dies, jigs, gauges, and tools, using machine tools, hand tools, or welders.
- Inspect finished dies for smoothness, contour conformity, and defects.
- Select metals to be used from a range of metals and alloys, based on properties such as hardness or heat tolerance.
- Lift, position, and secure machined parts on surface plates or worktables, using hoists, vises, v-blocks, or angle plates.
- File, grind, shim, and adjust different parts to properly fit them together.
- Smooth and polish flat and contoured surfaces of parts or tools, using scrapers, abrasive stones, files, emery cloths, or power grinders.
- Measure, mark, and scribe metal or plastic stock to lay out machining, using instruments such as protractors, micrometers, scribes, or rulers.
- Conduct test runs with completed tools or dies to ensure that parts meet specifications, making adjustments as necessary.

**Emerging tasks** (O*NET):
- Troubleshoot malfunctions in manufacturing equipment.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mechanical _(knowledge)_
- Visualization _(ability)_
- Near Vision _(ability)_
- Problem Sensitivity _(ability)_
- Mathematics _(knowledge)_
- Production and Processing _(knowledge)_
- Design _(knowledge)_
- Manual Dexterity _(ability)_
- Finger Dexterity _(ability)_
- Control Precision _(ability)_
- Operations Monitoring _(transferable_skill)_
- Operation and Control _(transferable_skill)_

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

**Tools & technology:**
- Autodesk AutoCAD _(hot technology)_
- Bentley MicroStation _(hot technology)_
- Dassault Systemes SolidWorks _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Project _(hot technology)_
- Microsoft Word _(hot technology)_
- SAP software _(hot technology)_
- 1CadCam Unigraphics
- Autodesk Inventor

## AI exposure & outlook

- **AI task-overlap index:** 29th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 34th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 31st percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 25th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 69th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -10.8% growth (Declining); 4.7k annual openings; 55.2k → 49.3k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $63,180; 55,130 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-51-4111-00_