Computer vision engineer

Code 2511.2

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.

Essential skills

Knowledge

  • Python (computer programming)
  • machine learning
  • statistics
  • principles of artificial intelligence
  • computer programming
  • integrated development environment software
  • digital image processing

Skills and competences

  • implement data quality processes
  • define technical requirements
  • develop data processing applications
  • develop software prototype
  • establish data processes
  • manage data collection systems
  • handle data samples
  • normalise data
  • proporcionar documentación técnica
  • deliver visual presentation of data
  • conduct literature research
  • perform data cleansing
  • perform dimensionality reduction
  • use software libraries
  • utilise computer-aided software engineering tools

Transversal competences

  • apply statistical analysis techniques
  • execute analytical mathematical calculations
  • report analysis results
  • interpret current data

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What to assess for this role

Technical knowledge can be verified with tests and references. What never shows up on a CV are the transversal competences, and they explain most failed hires. Before closing, it pays to measure them with a standardised battery.

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Sources

This service uses the ESCO classification of the European Commission and the Mapha Taxonomy developed by OTIC SOFOFA (CC BY 4.0), in an adapted version. Group codes come from the ILO's ISCO-08. See sources and licences