Machine learning

Machine learning is one of the fields of artificial intelligence that is broadly defined as a machine’s ability to imitate the intelligent behaviour of a human. Artificial intelligence systems are used for performing complex tasks in a way similar to that in which humans solve problems. It was defined in the 1950s by Arthur Samuel, an artificial intelligence pioneer, as ‘the field of study that gives computers the ability to learn without being explicitly programmed’.

Who teaches the machines?

The goal of AI is to create the computer models that exhibit ‘intelligent behaviour’ similar to that of humans. In practice, it means machines that are able to recognise visual scenes, understand text written in natural language or perform a task in the physical world.

But who will teach the machines to think and act like humans?

Speech specialist

Develops and improves speech recognition systems, focusing on linguistic aspects, such as pronunciation, intonation and accent.

Computational linguist

Creates models and algorithms that are able to analyse and understand human language and to recognise speech and text.

Machine translation engineer

Develops, builds and implements machine translation models and systems. Designs and introduces MT models, taking into account linguistic subtleties and complexities.

NLP researcher

Uses linguistic theories and methods for tasks associated with natural-language processing, such as machine translation, sentiment analysis and text classification.

NLP engineer

Builds NLP systems that use linguistic knowledge and experience to improve accuracy and efficiency. Develops and refines natural-language processing techniques for translation, such as language modelling or neural machine translation.

Project Manager

Manages projects in which machine translation systems are used, being responsible for quality, efficiency and accuracy.

Linguistic data annotator

Creates multilingual data sets and annotates them with linguistic information, such as parts of speech tags, syntax structures and semantic relations used for training and assessing machine translation models.

Data validator

Collects data and assesses their quality in terms of their application in AI training.

Data validator

Collects data and assesses their quality in terms of their application in AI training.


Carries out research on machine translation and creates the new algorithms and models to develop this field.

Multilingual content manager

Creates and manages multilingual content, such as websites and multimedia documents or content, to ensure their accuracy, consistency and cultural adequacy.

Technical writer

Translates technological aspects into language that is understandable to end-users. Creates manuals, technical documentation and other materials associated with machine translation systems and tools.

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    linguistic outsourcing

    Linguistic support for AI

    These are only a few examples of the many roles in the field of machine learning. Specific responsibilities, skills and qualifications will differ depending on the type of work and industry.

    We employ experts specialised in various fields who can help your company use artificial intelligence.


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