# Ophthalmic Laboratory Technicians

> Cut, grind, and polish eyeglasses, contact lenses, or other precision optical elements. Assemble and mount lenses into frames or process other optical elements. Includes precision lens polishers or grinders, centerer-edgers, and lens mounters.

- **SOC code:** 51-9083.00
- **Canonical URL:** https://singulariki.com/roles/role-51-9083-00
- **Also known as:** Lab Technician (Laboratory Technician), Optical Lab Technician (Optical Laboratory Technician), Optical Technician, Surfacing Technician, Edger Technician, Finishing Lab Technician, Lens Grinder and Polisher, Line Operator
- **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):
- Mount and secure lens blanks or optical lenses in holding tools or chucks of cutting, polishing, grinding, or coating machines.
- Inspect lens blanks to detect flaws, verify smoothness of surface, and ensure thickness of coating on lenses.
- Set up machines to polish, bevel, edge, or grind lenses, flats, blanks, or other precision optical elements.
- Inspect, weigh, and measure mounted or unmounted lenses after completion to verify alignment and conformance to specifications, using precision instruments.
- Shape lenses appropriately so that they can be inserted into frames.
- Clean finished lenses and eyeglasses, using cloths and solvents.
- Mount, secure, and align finished lenses in frames or optical assemblies, using precision hand tools.
- Examine prescriptions, work orders, or broken or used eyeglasses to determine specifications for lenses, contact lenses, or other optical elements.
- Adjust lenses and frames to correct alignment.
- Select lens blanks, molds, tools, and polishing or grinding wheels, according to production specifications.
- Position and adjust cutting tools to specified curvature, dimensions, and depth of cut.
- Assemble eyeglass frames and attach shields, nose pads, and temple pieces, using pliers, screwdrivers, and drills.

**Emerging tasks** (O*NET):
- Tint lenses according to customer specifications.

## Skills, tools, capabilities

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

**Skills in demand:**
- Finger Dexterity _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Mathematics _(Common Skill)_
- Visualization _(Specialized Skill)_
- Time Management _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Speech Recognition _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Microsoft Word _(Common Skill)_
- Microsoft PowerPoint _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_
- SAP software _(hot technology)_
- Electronic medical record EMR software
- Eyeglass design software

## AI exposure & outlook

- **AI task-overlap index:** 22nd percentile (Low) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 32nd percentile (Low) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 24th percentile (Low) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 15th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 94th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 2.3% growth (About average); 2.4k annual openings; 19.6k → 20k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $38,420; 18,740 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-51-9083-00_