# Bioengineers and Biomedical Engineers

> Apply knowledge of engineering, biology, chemistry, computer science, and biomechanical principles to the design, development, and evaluation of biological, agricultural, and health systems and products, such as artificial organs, prostheses, instrumentation, medical information systems, and health management and care delivery systems.

- **SOC code:** 17-2031.00
- **Canonical URL:** https://singulariki.com/roles/role-17-2031-00
- **Also known as:** Biomedical Engineer, Biomedical Technician (Biomedical Tech), Process Engineer, Research Engineer, Engineer, Analytical Biochemical Engineer, Biochemical Development Engineer, Biochemical Engineer
- **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):
- Evaluate the safety, efficiency, and effectiveness of biomedical equipment.
- Prepare technical reports, data summary documents, or research articles for scientific publication, regulatory submissions, or patent applications.
- Design or develop medical diagnostic or clinical instrumentation, equipment, or procedures, using the principles of engineering and biobehavioral sciences.
- Conduct research, along with life scientists, chemists, and medical scientists, on the engineering aspects of the biological systems of humans and animals.
- Adapt or design computer hardware or software for medical science uses.
- Develop statistical models or simulations, using statistical or modeling software.
- Maintain databases of experiment characteristics or results.
- Read current scientific or trade literature to stay abreast of scientific, industrial, or technological advances.
- Manage teams of engineers by creating schedules, tracking inventory, creating or using budgets, or overseeing contract obligations or deadlines.
- Develop models or computer simulations of human biobehavioral systems to obtain data for measuring or controlling life processes.
- Design or conduct follow-up experimentation, based on generated data, to meet established process objectives.
- Write documents describing protocols, policies, standards for use, maintenance, and repair of medical equipment.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Engineering and Technology _(knowledge)_
- Computers and Electronics _(knowledge)_
- Mathematics _(knowledge)_
- Inductive Reasoning _(ability)_
- Reading Comprehension _(essential_skill)_
- Active Listening _(essential_skill)_
- Writing _(essential_skill)_
- Speaking _(essential_skill)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Oral Expression _(ability)_
- Written Expression _(ability)_

**Skills in demand:**
- Mathematics _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Writing _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- Physics _(Specialized Skill)_
- Information Ordering _(Specialized Skill)_
- Critical Thinking _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Biology _(Specialized Skill)_
- English Language _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- Python _(hot technology, in demand)_
- R _(hot technology, in demand)_
- Adobe Illustrator _(hot technology)_
- Adobe Photoshop _(hot technology)_
- Autodesk AutoCAD _(hot technology)_
- C _(hot technology)_
- C++ _(hot technology)_
- Dassault Systemes SolidWorks _(hot technology)_
- Extensible markup language XML _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 88th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 73rd percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 86th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 89th percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 21st percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 5.2% growth (About average); 1.3k annual openings; 22.2k → 23.3k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $106,950; 21,860 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 10% automation, 69% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** learning.

**Tasks most handed to AI here:**
- Teach biomedical engineering or disseminate knowledge about the field through writing or consulting. _(1.2% of measured AI use; learning)_
- Conduct research, along with life scientists, chemists, and medical scientists, on the engineering aspects of the biological systems of humans and animals. _(0.9% of measured AI use; learning)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me teach biomedical engineering or disseminate knowledge about the field through writing or consulting.
- Help me conduct research, along with life scientists, chemists, and medical scientists, on the engineering aspects of the biological systems of humans and animals.

## 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-17-2031-00_