# Rail Car Repairers

> Diagnose, adjust, repair, or overhaul railroad rolling stock, mine cars, or mass transit rail cars.

- **SOC code:** 49-3043.00
- **Canonical URL:** https://singulariki.com/roles/role-49-3043-00
- **Also known as:** Rail Car Mechanic, Rail Car Repairer, Rail Car Repairman, Rail Car Welder, Freight Maintenance Specialist, Locomotive Repairman, Rail Car Maintenance Mechanic, Rail Car Sandblaster
- **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 conditions of cars, and repair and maintenance work performed or to be performed.
- Inspect components such as bearings, seals, gaskets, wheels, and coupler assemblies to determine if repairs are needed.
- Repair or replace defective or worn parts such as bearings, pistons, and gears, using hand tools, torque wrenches, power tools, and welding equipment.
- Inspect the interior and exterior of rail cars coming into rail yards to identify defects and to determine the extent of wear and damage.
- Remove locomotives, car mechanical units, or other components, using pneumatic hoists and jacks, pinch bars, hand tools, and cutting torches.
- Test units for operability before and after repairs.
- Adjust repaired or replaced units as needed to ensure proper operation.
- Repair and maintain electrical and electronic controls for propulsion and braking systems.
- Disassemble units such as water pumps, control valves, and compressors so that repairs can be made.
- Repair, fabricate, and install steel or wood fittings, using blueprints, shop sketches, and instruction manuals.
- Measure diameters of axle wheel seats, using micrometers, and mark dimensions on axles so that wheels can be bored to specified dimensions.
- Perform scheduled maintenance, and clean units and components.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mechanical _(knowledge)_
- Troubleshooting _(transferable_skill)_
- Repairing _(transferable_skill)_
- Arm-Hand Steadiness _(ability)_
- Manual Dexterity _(ability)_
- Control Precision _(ability)_
- Equipment Maintenance _(transferable_skill)_
- Multilimb Coordination _(ability)_
- Finger Dexterity _(ability)_
- Near Vision _(ability)_
- Problem Sensitivity _(ability)_
- Reaction Time _(ability)_

**Skills in demand:**
- Equipment Maintenance _(Specialized Skill)_
- Finger Dexterity _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Visualization _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Deductive Reasoning _(Common Skill)_
- Mathematics _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft Windows _(Common Skill)_
- Microsoft PowerPoint _(Common Skill)_
- Microsoft Outlook _(Common Skill)_

**Tools & technology:**
- Adobe Acrobat _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Windows _(hot technology)_
- Microsoft Word _(hot technology)_
- Mozilla Firefox _(hot technology)_
- Disassembler software _(in demand)_
- Microsoft Internet Explorer
- RailTech Software Solutions Rail 21 Management System
- RailTech Software Systems Mars for the 21st Century

## 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.):** 6th percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 17th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 8th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 75th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 2.8% growth (About average); 1.5k annual openings; 17.9k → 18.4k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $65,680; 18,300 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-49-3043-00_