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How to write a machine learning job description


Crafting the perfect job description for a machine learning engineer role is no small task. The technical requirements evolve with the industry and change based on seniority. This makes it challenging to ensure your job description is up to date, compliant with laws and regulations, and attractive to top candidates. 

A good job description does more than just list hard skills. It provides a holistic view of the role, capturing essential skills and presenting your company's values in a compelling way. On the flip side, a job description without these elements can cost you top talent and leave you trailing behind competitors.

This guide simplifies your hiring process by helping you create a job description that lists essential skills and presents your company in a good light.

What is a machine learning engineer?

A machine learning engineer is a professional who uses computer programming to develop intelligent software programs that gather data, learn from it, and make predictions. 

With data science and software engineering backgrounds, these experts play a crucial role in automating decision-making processes and driving innovations that can revolutionize industries. Their skills are essential for companies that want to use data for competitive advantages and expansion.

Machine learning engineers can use multiple frameworks, such as TensorFlow, Keras, or PyTorch, to create machine learning models. TensorFlow is the most popular of these.

Check out our guide to writing a job description for a TensorFlow developer for more information about hiring an engineer who will use this framework.

6 key skills to look for in a machine learning engineer

Machine learning candidates generally need these six skills:

  1. Competency in programming languages like Python or Java

  2. Experience with machine learning libraries, such as TensorFlow 

  3. Strong background in data analysis and statistics

  4. Experience with data manipulation and interpretation

  5. Analytical thinking and problem-solving skills for dissecting complex data

  6. Excellent communication skills to convey complex concepts effectively

6 key skills to look for in a machine learning engineer graphic

How to write an effective machine learning engineer job description

Writing an attractive job description is essential to securing a candidate who resonates with your company's goals. Don’t just list the required technical skills. You also need to convey your organization's values and mission. 

Describe your company’s culture and perks

Showcase your company's culture by describing core values, such as integrity and innovation. Highlight the distinct benefits of the role, like paid sabbaticals or unlimited paid time off, and emphasize growth opportunities and perks that make your company stand out. 

This will attract candidates who resonate with your company’s mission and feel drawn to an environment where they can belong, thrive, and make a meaningful impact.

Make your job description detailed

A detailed description of the responsibilities and expectations of the role will help you avoid a mis-hire. You should also provide a realistic depiction of the day-to-day tasks so your candidates know what they’ll do once hired.

In addition, a good job description should demonstrate clarity and transparency in your hiring process. This helps you to attract the best candidates and ensures you stay compliant with employment regulations and legal requirements that might apply to you.

Champion inclusion and diversity

Emphasize inclusivity and diversity to foster a rich, welcoming working environment. You can do this by actively promoting and celebrating potential applicants' varied backgrounds, experiences, and perspectives. 

Also, it’s essential to comply with employment laws by using non-discriminatory language, ensuring that no candidates feel automatically disqualified because of their backgrounds or identities.

Get your employees involved

Testimonials from current employees can help potential candidates understand the benefits of working at your company. They help build trust and allow candidates to envision a fulfilling career with your company. 

Machine learning engineer job description template

A well-written machine learning job description should have the following components:

1. Company introduction

Provide a brief overview of your company's values, core areas of business, and mission. 

Mention the company's date of creation and significant achievements, and discuss how machine learning plays an essential role in its objectives. Highlight any key innovations or cutting-edge technology that sets your company apart in its industry. 

2. Benefits of working with your company

Detail the different benefits of being a part of your organization, including competitive compensation, health benefits, and retirement plans. Emphasize perks like continuous learning opportunities and flexible work arrangements.

Other benefits you might mention include your support for work-life balance, a collaborative work environment, or pathways for career progression.

3. Job brief

[Company name]

Job Title: [For example, Senior Machine Learning Engineer or Junior Machine Learning Engineer]

Reports to: [For instance, Head of AI/ML Department]

Position type: [Full-time, part-time, on-site, remote, or hybrid]

[Salary and compensation details]

4. Responsibilities

  • Designing, developing, and deploying machine learning models

  • Analyzing large and complex data sets to extract actionable insights

  • Collaborating with data scientists and engineers to enhance data quality and efficiency

  • Staying aware of industry trends and adopting emerging technologies

  • [Other responsibilities based on your company’s specific needs]

5. Requirements, qualifications, and training

  • Bachelor’s/master’s degree in computer science, data science, or a related field

  • Proven experience in machine learning, data analysis, and programming

  • Proficiency in Python, Java, or [other coding languages or tools based on your company’s specific needs]

  • [Other qualifications based on your company’s specific needs]

Three things to avoid when crafting a job description

When writing your machine learning job description, be mindful of the following:

1. Being too vague

Vague job descriptions can attract unqualified candidates and deter skilled candidates from applying due to insufficient information. Avoid using generic terms and descriptions. Be specific about the role’s duties and the skills required to set clear expectations and ensure compliance with regulatory and legal standards, which often mandate transparent and accurate job descriptions.

2. Ignoring culture-add criteria

Don't overlook the importance of candidates’ personalities and behavior. Candidates who don’t mesh well with your team can cause breakdowns in team synergy and friction among colleagues. Mention the kind of work environment and team dynamics the candidate can expect so that those who won’t mesh can self-filter.

3. Neglecting career growth opportunities 

Failing to highlight growth opportunities in your organization may deter talented candidates. Top candidates are looking for roles where they can grow. Highlight the potential career paths and development opportunities that come with the position.

Next steps: Attracting and assessing machine learning candidates

After crafting a well-rounded job description, focus on advertising the role on your company’s website as well as platforms frequented by tech professionals, such as LinkedIn and GitHub. 

Then, use TestGorilla's multi-tier testing approach to assess machine learning talent. This approach, which combines a variety of tests into a single assessment, will help you objectively and thoroughly evaluate the various qualities your ideal candidate needs.

Add personality and culture-add tests to gain an even deeper understanding of each candidate and their suitability for the role. 

For instance, TestGorilla’s Machine Learning assessment is a comprehensive sample of a data science test that helps you easily identify candidates versed in ML. In contrast, an Enneagram test will help you understand candidates’ personality types and determine which fit best with your company culture.. 

By evaluating both technical proficiency and cultural alignment, you’ll significantly reduce the chances of a mis-hire.


What salary range should I include in my job description?

As of 2023, the average annual salary of machine learning engineers is $127,448. Include a range that accounts for factors like the role's seniority and your company's location. For example, entry-level positions should start slightly below the average, while senior roles command higher pay.

What career growth opportunities should I outline in my job description?

In your machine learning job description, highlight career growth opportunities, including:

  • Progression to senior or lead roles

  • Cross-functional collaboration with departments like data engineering or product management

  • Opportunities for specialized training and certifications

  • Mentorship opportunities

  • Involvement in cutting-edge projects 

Your blueprint to securing top talent with TestGorilla 

A skilled machine learning engineer can harness vast amounts of data, automate and optimize processes, and deliver predictive insights to help your company flourish. This is why securing top-notch talent using a well-written job description is essential. Your job description should be detailed and compelling so it appeals to the right applicants.

Once you’ve attracted applicants with your machine learning job description, use TestGorilla’s tests for machine learning engineers to find the best candidate for the role. 

Begin your journey to a successful hire by exploring more of our 300+ pre-employment assessments

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