The applications of Machine Learning Engineers are diverse: image recognition, facial recognition and analysis, language translation and personalised product recommendations are classic use cases. Today, the field of applications has greatly expanded, and most of the problems in this discipline can be solved by collecting data. It is primarily Big Data approaches that can lead to new innovative developments. That makes machine learning highly attractive for companies to develop new products and services.
Through our expertise in digital HR consulting and executive search, our recruiters are able to find the right candidates for your specific requirement profile. Thanks to market and feasibility analyses, we can quickly present you with the first candidates.
Machine Learning Engineers are the interface between data science and software engineering - data meets programming. They help develop products with artificial intelligence, and have excellent knowledge of statistics and programming. Above all, they have one thing in common: they are real problem solvers. They are fascinated and motivated by the challenge of both discovering and recognising patterns that others are unable to see. They have to turn the unknown into the familiar and make better decisions to achieve better results.
The responsibilities of Machine Learning Engineers depend on the particular project they are working on. There are three categories they fall into:
Core Machine Learning Engineer
This type of Machine Learning Engineer is expected to have strong computer science and programming skills and to focus more on data modelling and analysis and the application of machine learning algorithms and libraries. Practical work includes for example the development and improvement of development tools and software libraries for Deep Learning.
Applied Machine Learning Engineer
This job also requires a sound knowledge of computer science, focusing on the application of machine learning algorithms and libraries. In practice, data mining, machine learning and graph analysis techniques are used and applied to a variety of modelling, relevance and recommendation problems.
Software Engineer - Machine Learning
Unlike Core and Applied Machine Learning Engineers who spend more time applying algorithms and modelling data, Software Engineers specialising in machine learning spend more time developing software and designing systems. Practical applications include optimising rankings and recommendations of localised results using machine learning algorithms.
In addition to all the hard skills, machine learning engineers also bring a number of soft skills that are becoming increasingly important for organisations. These include the ability to communicate clearly and comprehensibly, teamwork, leadership qualities in terms of employee motivation as well as the role of being a mentor and, last but not least, an impeccable work ethic.
The market is booming in this field and knowledgeable experts are in high demand. We are happy to advise you with our digital know-how, find the ideal candidate for you and support the digital development of your company.
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