Machine Learning is an increasingly relevant domain within almost any industry, especially in tech driven businesses.

The statistics show that 3.92% of the IT jobs in the end of 2021 and beginning 2022 were related to Machine Learning. This figure has been growing at almost 10% in the last year. And Machine Learning engineers get offered an average annual salary of $93.000 (IT Jobs Watch, UK, 2022). In the United States the reported average yearly salary of a Machine Learning engineer even goes up to $120.000 (Glassdoor, 2021).

Moving between hype and 

Gartner places Machine Learning between the peak of inflated expectations and trough of disillusionment, meaning that Machine Learning is currently still a hype but people also look at it increasingly more critically.

So what do we make of this when you’re looking to hire Machine Learning experts? 

In this blog we’ll give some guidance on:

1. Who Machine Learning engineers are
2. Where you can find them
3. How to hire them

1. Who are Machine Learning engineers?

Machine Learning engineers are typically strong software programmers who also have a good understanding of data models and more specifically learning models.

They research, build and test learning algorithms that they deploy in digital products that are self learning or within companies that use those models to improve processes.

Machine Learning experts typically work on the crossroads between data science, engineering and DevOps related activities.

‍Some of the most important activities of a Machine Learning engineer:

• Engineering models and data solutions
• Deploy data modelling and analysis to find patterns within the data 
• Algorithm selection and implementation
• Researching and implementing ML tools
• Selecting data sets and possibly cleaning them for use
• Validating and testing algorithms

Most important skills of a Machine Learning engineer:

• Math and statistics skills
• Strong analytical and problem-solving skills
• Software engineering skills like Python, Java, C++, C, R and JavaScript
• Understand data structures and data modelling
• Knowledge in computer architecture