Guide on how to hire a machine learning engineer

Recruiting highly skilled machine learning engineers can help you harness the power of artificial intelligence (AI) and gain a competitive edge in today’s data-driven world. 

But to make a great hire, you’ll need to understand how to define your job requirements,  be able to identify and attract top talent, and properly assess candidates’ skills. Failing to do so can leave you with a new hire who isn’t suitable for your position, leading to project delays, higher costs, and decreased overall business efficiency. 

To help you ensure you pick the best candidate for your open role, we’ve compiled this guide on how to hire a machine learning engineer.

Looking for a TensorFlow machine learning developer? Check out our full guide on hiring great TensorFlow developers.

What you need to know before hiring a machine learning engineer

Before you start looking for a machine learning engineer, you must clearly understand what your role requires and how much you need to pay. 

Understanding the requirements of your role

To hire the best candidate for your open position, you need to know what you’re looking for. Think about the following:

• The essential skills candidates need to have

• Optional skills that will be useful in the role

• What the new employee’s role in your company will be

• Whether leadership or management abilities are needed

• Any qualifications that are required

• Whether you require a specific level of experience (professional or academic)

You should also consider a candidate’s culture add to ensure you hire someone whose beliefs and values align with your company’s. This can help prevent internal conflicts,  reduce staff turnover, and improve team morale.  

Establishing attractive compensation for machine learning engineers

Offering competitive compensation and benefits is essential since it will help you attract top talent. Numerous online sources can help you understand more about this.

For example, Glassdoor provides an annual compensation range of $121,000-$193,000 for machine learning engineers. It also lists an average base salary of $152,000 per year. Indeed provides a similar range, with a slightly higher average base salary of $160,140 annually. You can use this information to ensure you offer your machine learning candidates a competitive salary. 

Offering benefits like medical insurance, dental insurance, gym memberships, and performance-based bonuses can also help you attract high-quality applicants.

Skills and qualifications to look for in a machine learning engineer

Machine learning engineering is a specialist position, and potential candidates for a role should have a clear set of skills and qualifications. Here’s a closer look at what these are. 

Soft skills

Two of the most important soft skills for machine learning engineers are critical thinking and problem-solving. These enable individuals to approach a problem (or project) methodically, breaking it down into smaller components and developing clear solutions. 

In addition, you’ll want to look for strong communication skills to ensure candidates can explain technical concepts and insights from machine learning models in layperson’s terms. Strong collaboration skills are also useful in machine learning engineer roles, as these help individuals work well in a team and across departments.

Other essential soft skills for machine learning engineers include adaptability, time management, attention to detail, and creativity. 

TestGorilla offers various pre-employment tests to assess these skills, including the Problem Solving test, Critical Thinking test, and Attention to Detail (Textual) and (Visual) tests.

Hard skills

Machine learning engineers must possess various hard skills to do their jobs well.

First, they should be fluent in Python and other relevant programming languages, such as R or Julia. These are crucial for implementing machine learning algorithms and configuring them to meet your needs. 

Candidates should also have a strong understanding of machine learning algorithms and related concepts. A solid mathematical foundation and familiarity with big data technologies and cloud computing platforms are also very beneficial.

TestGorilla provides a wide range of hard skills tests for machine learning engineers, such as the Machine Learning test and the Algorithms for Software Engineering test. 

The exact hard skills to focus on will depend on how specific the role is. For example, the hard skills listed in a computer vision engineer job description will differ from those of a generic machine learning engineer

Qualifications 

Although qualifications aren’t mandatory for machine learning engineers, they help ensure you hire someone with the necessary skills for the job.

For starters, a bachelor’s or master’s degree in machine learning, data science, or computer science is a great qualification to look for. Certifications from machine learning or computer science bootcamps or courses can also demonstrate expertise, especially in specific areas of machine learning.

Where to find skilled machine learning engineers

Machine learning engineers are in high demand, and this can make it difficult to attract interest from top talent. Because of this, you’ll need to diversify your recruiting efforts to ensure your role is visible to the largest candidate pool possible. 

Aside from the standard of posting your position on online job boards and websites like LinkedIn and Indeed, there are several other ways to find machine learning engineers. 

Creative ways to find machine learning engineers

In online communities

Joining and engaging in online communities and forums is a fantastic way to connect with machine learning engineers. Websites like Stack Overflow, Dev Community, and Reddit are great places to start. 

Begin by creating a profile on the site and joining the relevant communities and channels, such as the r/MachineLearning community on Reddit. Then, you can share posts, comment on others’ posts, and engage with machine learning engineers. 

Viewing the results of online competitions

Websites like Kaggle regularly run online competitions that attract talented machine learning engineers. Consider participating in or viewing the results of these competitions to identify individuals with robust skills and a passion for machine learning.

Then, you can contact them to see if they could become applicants and potential candidates for your open role.

How to select the best machine learning engineer candidates

Once you have a decent-sized candidate pool, you’ll need to begin filtering applications and identifying individuals that fit your requirements. The best way to do this is with a combination of screening assessments and machine learning interview questions that assess each candidate’s skills and experience in the field.  

Using specific machine learning skills tests as part of your screening process lets you evaluate and rank candidates at an early stage. With this information, you can immediately disqualify unsuitable profiles and narrow your candidate pool significantly. 

TestGorilla makes this quick and straightforward. You can create and deliver custom machine learning engineer assessments that candidates can complete from their mobile devices. Our platform has more than 300 expert-created skills tests, and you can combine up to five of these with custom interview questions. 

In particular, TestGorilla offers various tests for assessing machine learning engineers. These include the general Machine Learning test and the more specialized Machine Learning in Azure, Machine Learning in Google Cloud Platform, and Machine Learning in Amazon Web Services tests.  

You can also use data science assessments to evaluate your machine learning candidates. TestGorilla has a dedicated Data Science test and a range of related skills tests to help you do this.  

To gather a complete picture of an applicant's skills and personality, you can combine a couple of these tests with our personality or cognitive ability tests. For example, you could use the Culture Add test to assess a candidate’s values and behaviors and the Problem Solving test to evaluate how they think.

TestGorilla also lets you add one-way custom interview questions, which can provide excellent insights into a candidate’s skills, behaviors, and thought processes. Additionally, you can also use custom questions to hone in on skills that are important for your role.

Finally, you can rank candidates based on their assessment results through the TestGorilla app. This helps ensure you don’t overlook talented individuals who are a good fit for your role. 

Common mistakes when hiring a machine learning engineer

Be mindful of committing the following mistakes when hiring machine learning engineers for your team:

1. Misunderstanding the role

A major mistake many hiring managers and recruiters make when hiring machine learning engineers is not fully understanding the position's requirements. Since it’s a technical role, you’ll need to hone in on the skills and experience necessary to hire a skilled candidate.  

You can do this by sitting down and defining your role at the start of the hiring process. List essential and preferred qualifications and experience. Many machine learning positions, for example, require professionals to be familiar with specific technologies such as Amazon Web Services and Google Cloud. 

Also, remember that not all machine learning engineer positions are the same. Speak with your existing team to better understand what they do each day and the skills and knowledge that a candidate would need to succeed as a machine learning engineer at your company specifically. Incorporate this information into your job description and prioritize assessing these skills and traits during recruitment. 

2. Forgetting to consider real-world experience

Hands-on experience is incredibly valuable in machine learning, so avoid focusing solely on candidates’ theoretical knowledge. Instead, evaluate candidates based on their real-world experience.

During interviews, ask candidates about the projects they’ve worked on and the challenges they’ve faced (and how they overcame them). You might also consider providing them with practical exercises to assess their problem-solving skills and ability to put their knowledge into action in real time.

3. Overlooking adaptability

Machine learning is a constantly evolving field, and talented engineers must be willing to learn and adapt to new technologies. Individuals lacking in this can slow progress and stall your company. 

Thus, it’s important to remember to assess candidates’ adaptability. You can do this through a combination of custom interview questions and pre-employment testing.

How TestGorilla can help you hire the perfect machine learning engineer

Machine learning engineering is a highly skilled role, and it’s crucial to separate top talent from unsuitable applicants. To achieve this, you must understand the requirements of your position and the skills to look for in a great machine learning engineer. Then, you’ll need an easy way to evaluate your candidates’ skills and aptitudes. 

Pre-employment screening platforms like TestGorilla make it easier than ever to do this. You can use role-specific soft and hard skills tests combined with machine learning interview questions to accurately and efficiently identify the best candidates for your role. 

To learn more about how TestGorilla can help, check out our product tour, sign up for a live demo, or create a free account and try it yourself.