# Structural Metal Fabricators and Fitters

> Fabricate, position, align, and fit parts of structural metal products.

- **SOC code:** 51-2041.00
- **Canonical URL:** https://singulariki.com/roles/role-51-2041-00
- **Also known as:** Fabricator, Fitter, Layout Man, Ship Fitter, Metal Fabricator, Mill Beam Fitter, Small Parts Fabricator, Steel Fabricator
- **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 conformance of workpieces to specifications, using squares, rulers, and measuring tapes.
- Study engineering drawings and blueprints to determine materials requirements and task sequences.
- Position, align, fit, and weld parts to form complete units or subunits, following blueprints and layout specifications, and using jigs, welding torches, and hand tools.
- Lay out and examine metal stock or workpieces to be processed to ensure that specifications are met.
- Tack-weld fitted parts together.
- Move parts into position, manually or with hoists or cranes.
- Set up and operate fabricating machines, such as brakes, rolls, shears, flame cutters, grinders, and drill presses, to bend, cut, form, punch, drill, or otherwise form and assemble metal components.
- Mark reference points onto floors or face blocks and transpose them to workpieces, using measuring devices, squares, chalk, and soapstone.
- Position or tighten braces, jacks, clamps, ropes, or bolt straps, or bolt parts in position for welding or riveting.
- Lift or move materials and finished products, using large cranes.
- Set up face blocks, jigs, and fixtures.
- Align and fit parts according to specifications, using jacks, turnbuckles, wedges, drift pins, pry bars, and hammers.

**Emerging tasks** (O*NET):
- Troubleshoot and repair electrical or mechanical equipment.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mathematics _(knowledge)_
- Production and Processing _(knowledge)_
- Mechanical _(knowledge)_
- Arm-Hand Steadiness _(ability)_
- Near Vision _(ability)_
- Visualization _(ability)_
- Manual Dexterity _(ability)_
- Control Precision _(ability)_
- Multilimb Coordination _(ability)_
- Static Strength _(ability)_
- English Language _(knowledge)_
- Reading Comprehension _(essential_skill)_

**Skills in demand:**
- Microsoft Outlook _(Common Skill)_
- Mathematics _(Common Skill)_
- Visualization _(Specialized Skill)_
- English Language _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Finger Dexterity _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_

**Tools & technology:**
- Microsoft Outlook _(hot technology, in demand)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Word _(hot technology)_
- Computer aided design and drafting CADD software
- Dassault Systemes CATIA
- Tekla software
- Three-dimensional modeling software

## AI exposure & outlook

- **AI task-overlap index:** 6th percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 15th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 7th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 9th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 44th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -16.3% growth (Declining); 4.1k annual openings; 53.8k → 45k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $49,900; 53,380 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-51-2041-00_