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Machine Learning Engineer

A Machine Learning Engineer contributes to the development, implementation, and optimization of machine learning systems. They work in teams with other professionals, such as data scientists and programmers.

Machine Learning Engineer Job Profile

What is a Machine Learning Engineer?

A Machine Learning Engineer contributes to the development, implementation, and optimization of machine learning systems. They work in teams with other professionals, such as data scientists and programmers.

Machine Learning is one of the megatrends of the current technological era, and ML Engineers are in high demand as a result. Machine learning involves the ability of computer systems to independently analyze large datasets. This approach is based on experiences that are represented in the form of structured or unstructured data. ML systems identify patterns within these datasets and make predictions based on them. Machine learning is a subset of Artificial Intelligence and is providing valuable services in an increasing number of use cases. For example, online train information tools use past data to inform passengers about the expected occupancy levels.

AI systems offer tremendous added value, and without the expertise of Machine Learning Engineers, this technology would not be possible. Working closely with other IT experts, ML Engineers ensure that sophisticated algorithms effectively analyze datasets and provide accurate results. A Machine Learning Engineer acts as a teacher, training machine learning software solutions. The goal is for the systems to learn autonomously and continuously improve. The ML specialist creates the foundation for this to happen.

What Tasks Does A Machine Learning Engineer Have?

Machine Learning engineers are faced with a multifaceted job. They focus on the development, implementation, and optimization of relevant software solutions, while Data Analysts and Data Scientists concentrate more on data processing and analysis. However, there are various intersections between the different roles in the field of ML, and they cannot be precisely separated. It also happens that an ML Engineer takes on tasks of a Data Analyst alongside their core responsibilities.

The work of an ML Engineer is characterized by the following key areas:

  • Building data structures that form the basis of machine learning

  • Programming machine software solutions that independently evaluate the available data

  • Developing suitable algorithms

  • Supporting, maintaining, and controlling these ML systems

This list provides an initial impression of the typical tasks of an ML Engineer. In practice, the specific tasks can vary. This also depends on the extent of personnel resources. In larger teams, for example, ML engineers may focus exclusively on maintenance.

What Tools Does A Machine Learning Engineer Work With?

In most job and project descriptions, there are detailed specifications regarding the tools and programming languages that an ML Engineer should master. Frequently, employers or clients require knowledge in the following areas:

  • Java

  • Python

  • Scala

  • Workflow Automation
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The Required Profile Of A Machine Learning Engineer

An ML Engineer should possess various hard and soft skills. Among the hard skills, appropriate education is important. Many ML specialists have completed the following degree programs:

  • Computer Science or Business Informatics

  • Mathematics or Applied Mathematics

  • Engineering sciences

Basically, even career changers can earn money as a Machine Learning Engineer, especially as freelancers who have good chances of starting a career. It is important that they have acquired sufficient expertise in fields such as computer science and statistics. Additionally, they should be familiar with tasks such as programming. For those who are unsure, they can, for example, buy a specialized book on Machine Learning or the corresponding profession: Interested individuals will quickly realize through reading whether they are up for this challenge.

In terms of soft skills, communicative abilities, English language proficiency, willingness to learn, and flexibility are important. ML engineers should be able to collaborate seamlessly with other specialists such as data scientists. The development of AI systems is teamwork! Specifically, freelancers should also be able to adapt to new projects and work situations. Good knowledge of the English language is indispensable in this field of work!

Machine Learning Engineer And Similar Roles Compared

We have already determined that there are overlaps between the profession of an ML engineer and other roles such as data scientist and data analyst. The boundaries are fluid. Nonetheless, there are different emphases that we would like to briefly illuminate.

For example, a data scientist extensively deals with data analysis and data visualization. Proficiency in these fields as well as in statistics proves to be particularly important. On the other hand, a machine learning engineer requires excellent programming skills and focuses on the implementation of machine learning. They work directly on and with these systems, identify areas for optimization, and propose suitable solutions.

How Much Does A Machine Learning Engineer Earn?

In the case of ML engineers, like in all IT professions, there is a wide range of earning possibilities. In general, these specialists can expect an attractive income, whether they are employed full-time or working as freelancers. The reason for these positive earning prospects is evident: machine learning and AI systems have tremendous potential, accelerating digitization processes to an unprecedented extent. Therefore, software developers and users are investing heavily in this field, desperately seeking experts and willing to pay a premium for their support.

Full-time machine learning engineers can expect a starting salary of around 50,000 euros. However, this figure serves as a rough guideline, as it depends on various factors. The same applies to freelancers. The following aspects, among others, influence the fixed salary or compensation for projects performed by self-employed individuals:

  • Qualifications of the ML engineer

  • Size and financial strength of the employer or client

  • Job or project description

  • Negotiating skills of the employee or freelancer

For instance, ML engineers with a master’s degree have better income prospects compared to those with a bachelor’s degree or career changers. Generally, larger companies tend to pay more than small and medium-sized enterprises (SMEs), but there are exceptions depending on specific circumstances. The ML and AI market is populated by many startups, some of which have received substantial investments. These startups also offer high salaries and compensations.

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