# Health and Safety Engineers, Except Mining Safety Engineers and Inspectors

> Promote worksite or product safety by applying knowledge of industrial processes, mechanics, chemistry, psychology, and industrial health and safety laws. Includes industrial product safety engineers.

- **SOC code:** 17-2111.00
- **Canonical URL:** https://singulariki.com/roles/role-17-2111-00
- **Also known as:** Product Safety Engineer, Safety Engineer, Safety and Health Consultant, System Safety Engineer, Health and Safety Specialist, Industrial Hygienist, Industrial Safety Engineer, Product Safety Consultant
- **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):
- Investigate industrial accidents, injuries, or occupational diseases to determine causes and preventive measures.
- Conduct research to evaluate safety levels for products.
- Evaluate product designs for safety.
- Conduct or coordinate worker training in areas such as safety laws and regulations, hazardous condition monitoring, and use of safety equipment.
- Maintain and apply knowledge of current policies, regulations, and industrial processes.
- Recommend procedures for detection, prevention, and elimination of physical, chemical, or other product hazards.
- Report or review findings from accident investigations, facilities inspections, or environmental testing.
- Evaluate potential health hazards or damage that could occur from product misuse.
- Evaluate adequacy of actions taken to correct health inspection violations.
- Interpret safety regulations for others interested in industrial safety, such as safety engineers, labor representatives, and safety inspectors.
- Review plans and specifications for construction of new machinery or equipment to determine whether all safety requirements have been met.
- Participate in preparation of product usage and precautionary label instructions.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Inductive Reasoning _(ability)_
- Reading Comprehension _(essential_skill)_
- Oral Comprehension _(ability)_
- Deductive Reasoning _(ability)_
- English Language _(knowledge)_
- Written Comprehension _(ability)_
- Oral Expression _(ability)_
- Problem Sensitivity _(ability)_
- Engineering and Technology _(knowledge)_
- Active Listening _(essential_skill)_
- Writing _(essential_skill)_
- Critical Thinking _(essential_skill)_

**Skills in demand:**
- Inductive Reasoning _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- English Language _(Common Skill)_
- Writing _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_
- Systems Analysis _(Specialized Skill)_
- Complex Problem Solving _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft SharePoint _(Specialized Skill)_

**Tools & technology:**
- Autodesk AutoCAD _(hot technology, in demand)_
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Outlook _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- Microsoft SharePoint _(hot technology, in demand)_
- Microsoft Word _(hot technology, in demand)_
- C++ _(hot technology)_
- Eclipse IDE _(hot technology)_
- Linux _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Active Server Pages ASP _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 74th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 74th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 68th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 77th percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 17th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 4.4% growth (About average); 1.5k annual openings; 23.8k → 24.9k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $109,660; 23,220 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/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **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-17-2111-00_