---
name: computer-vision-engineer
description: "Occupational skill for the role 'computer vision engineer' (also: computer vision applied scientist, computer vision expert, computer vision specialist, computer vision project engineer, smart technics computer vision engineer). Use when the user asks for typical computer vision engineer work such as: Analyze, manipulate, or process large sets of data using statistical software.; Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.; Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods."
---

# Computer Vision Engineer

Computer vision engineers research, design, develop, and train artificial intelligence algorithms and machine learning primitives that understand the content of digital images based on a large amount of data. They apply this understanding to solve different real-world problems such as security, autonomous driving, robotic manufacturing, digital image classification, medical image processing and diagnosis, etc.

## Core workflow

1. Analyze, manipulate, or process large sets of data using statistical software.
2. Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
3. Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
4. Clean and manipulate raw data using statistical software.
5. Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
6. Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.
7. Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.
8. Design surveys, opinion polls, or other instruments to collect data.

## How to use this skill

- Read `references/profile.md` for the occupation profile and scope.
- Consult `references/tasks.md` for the full task and activity inventory.
- Check `references/skills.md` for essential vs. optional competences.
- Check `references/tools.md` for the software commonly used in this role.

## Key competences (essential)

- apply statistical analysis techniques
- computer programming
- computer simulation
- conduct literature research
- data engineering
- data science
- define technical requirements
- deliver visual presentation of data
- develop computer vision system
- develop data processing applications
- develop software prototype
- digital image processing
- digital twin technology
- establish data processes
- execute analytical mathematical calculations

## Hot technologies

- IBM SPSS Statistics
- SAS
- TensorFlow
- The MathWorks MATLAB
- Docker
- GitHub
- Kubernetes
- Alteryx software
- Apache Spark
- Google Looker Analytics

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*Sources: ESCO v1.2.1 (http://data.europa.eu/esco/occupation/1c5a45b9-440e-4726-b565-16a952abd341), O*NET 30.3 (15-2051.00). See manifest.json for licensing/attribution.*
