The Job Market for Machine Learning Engineers in 2023: An In-depth Analysis of Over 1,000 LinkedIn Job Listings
The Job Market for Machine Learning Engineers in 2023: An In-depth Analysis of Over 1,000 LinkedIn Job Listings
ML engineers play a crucial role in developing various widespread technologies, such as natural language processing, computer vision, speech recognition, fraud detection, recommendation systems, etc.
With recent developments in AI, the machine learning engineer job outlook is brighter than ever. Now is the perfect time to join the field. But what skills are needed to beat the growing competition and succeed in this demanding field?
We analyzed over 1,000 job offers on LinkedIn to determine what employers offer and look for in ML engineer specialists in 2023.
The ML Engineer Job Outlook: Key Findings
- The demand for AI and ML specialists will grow by 40% from 2023 to 2027.
- The average ML engineer’s salary is $133,336/year.
- The most sought-after degree for ML engineer positions is computer science.
- 8% of ML engineer job offers require Python.
- The most required Python libraries for ML engineers are TensorFlow, Keras, and scikit-learn.
- 8% of ML engineer jobs are in the IT services and consulting sector.
- 6% of ML engineer job ads are for entry-level positions.
The ML Engineer Job Outlook in 2023: Table of Contents
- Methodology
- What Does a Machine Learning Engineer Do?
- Where Do ML Engineers Work?
- How to Become a Machine Learning Engineer
- How Much Do ML Engineers Make?
- What Is the Machine Learning Engineer Job Outlook in 2023?
- Starting an ML Engineering Career
- FAQs
Methodology
Our initial search for ML engineer jobs on LinkedIn generated 1,032 results. Since we aimed to solely analyze the machine learning engineer job outlook, we excluded irrelevant results, such as data scientist positions. All findings below are based on the remaining 714 machine learning engineer offers extracted from LinkedIn in December 2022.
What Does a Machine Learning Engineer Do?
Machine learning engineers design, implement, and maintain artificial intelligence systems. The role requires advanced computer science and data science skills and a solid understanding of mathematics and statistics.
The machine learning engineer job description involves creating data models, training and testing machine learning algorithms, deploying AI systems into production, evaluating and optimizing existing solutions, etc.
Still, the job requirements vary depending on the organization’s goals, function, industry, and size. And although AI solutions are starting to find applications everywhere, the demand for ML engineering jobs is higher in some industries, companies, and locations than in others.
Where Do ML Engineers Work?
The 714 ML engineer positions in our study were posted by 368 companies across 142 industries and 37 states. Let’s examine the ones with the most job offers.
Companies with the Most Machine Learning Engineer Job Offers
The companies with the most ML engineer openings are technology and recruitment firms. The top ten by the number of open positions include:
- Apple – a multinational technology company
- Diverse Lynx – a staffing and consulting firm
- SynergisticIT – a software solutions, development, and IT upskill organization
- Grammarly – a cloud-based spelling, grammar, and punctuation detection system
- CyberCoders – a leading recruitment firm
- Acceler8 Talent – a tech recruitment company
- Adobe – a computer software company
- Emonics LLC – an IT staffing and consulting organization
- Fidelity Investments – a financial services corporation
- Zoom – a communications technology company
We also encountered big names like Netflix, Tinder, Roche, Cigna, TikTok, Pinterest, Ford Motor Company, Siemens, Shuttlerock, and Uber.
Industries with the Most Machine Learning Engineer Job Offers
What is the distribution of job offers by industry?
Unsurprisingly, the most significant number of ML engineer positions were available in technology and internet-related sectors. The demand for specialists is also high in different types of manufacturing industries.
We also encountered job openings in airlines and aviation, wellness and fitness services, mental health care, non-profit organizations, research services, etc., but these were individual cases.
Locations with the Most Machine Learning Engineer Job Offers
Our job search was limited to the US, but 171 ads did not specify the state. The distribution of the rest includes the following:
California holds the overwhelming majority. The rest of the top 10 states with the most machine learning jobs include Texas, Washington, New York, Massachusetts, Illinois, Florida, North Carolina, Ohio, and Virginia.
How to Become a Machine Learning Engineer
ML engineering is a highly specialized role requiring skills and knowledge in various disciplines. The typical machine learning engineer career path involves prior experience as a software engineer or an academic background.
Still, there are various paths one can follow to get into the field. And anyone with the necessary education and skills can become a machine learning engineer. Although the requirements have changed slightly in the past few years (see our 2020 research), the basics remain the same.
Machine Learning Engineer Education Requirements
Most machine learning engineer jobs require higher education. But since this role involves a diverse skill set and knowledge in various areas, employers accept several backgrounds.
The most sought-after degree for machine learning engineer positions is computer science. Engineering is a close second. Other related fields—such as data science, mathematics, statistics, and data engineering—are also valuable.
All these disciplines teach essential knowledge for the role. And while holding one of these degrees gives you a head start, there’s much more to learn. So, regardless of your qualifications, you must acquire all relevant skills to become a machine learning engineer.
Machine Learning Engineer Skills Requirements
ML engineer positions require solid technical and theoretical knowledge.
Deep learning is among the most desired capabilities. Some employers look specifically for neural network or computer vision skills, while others mention concrete ML techniques like reinforcement learning, supervised learning, and clustering.
And, of course, most ads feature concrete technical requirements. Machine learning engineering involves programming, and the most required coding language is Python, which is mentioned in over two-thirds of job offers.
Some employers will also list concrete ML Python libraries like TensorFlow, Keras, scikit-learn, and Theano.
Whether at the beginning of your machine learning journey or as a practitioner looking to upskill, our ML bundle will help you acquire the most sought-after skills. Ken Jee and Jeff Li teach you everything about the ML process, algorithms, and business applications in a series of courses.
How Much Do ML Engineers Make?
According to Glassdoor, the average machine learning engineer salary is $133,336/year (bonuses included). And while almost all LinkedIn job postings in our sample are for full-time jobs, freelancing is also a viable and well-paid option. ZipRecruiter reports that the average annual pay of a freelance ML engineer is $132,138.
In addition, earnings and responsibilities depend on one’s experience. Most job offers in our sample were for entry- and mid-senior-level machine learning engineer jobs. Almost a third of the ads did not specify the seniority level; the rest were for associate or director positions.
And the salaries vary according to the seniority level.
- Entry-level (intern): $103,258/year
- Mid-senior level: $133,336/year
- Senior: $167,277/year
- Director: $214,227/year
Other factors (the firm’s size, location, industry, and primary function) influence earnings. For example, a machine learning expert’s salary can reach \$225,990/year at Meta, \$215,805/year at Google, and \$212,260/year at Twitter. And while these are the top-paying companies for this position, machine learning engineering is a lucrative career choice.
What Is the Machine Learning Engineer Job Outlook in 2023?
Even in light of the recent tech layoffs and technological advancements, the future of machine learning engineers is bright. The demand for qualified AI and ML professionals is at an all-time high and will continue to grow.
AI already affects the work landscape, but this change is not necessarily detrimental to all roles. While some jobs will be automated and potentially replaced, others will be augmented, and ML engineering will likely be among the latter.
The World Economic Forum’s prognosis about the machine learning job market (2023–2027) is highly favorable. According to the Future of Jobs Report 2023, “Demand for AI and machine learning specialists is expected to grow by 40%, or 1 million jobs, as the usage of AI and machine learning drives continued industry transformation.”
ML engineering is and will remain one of the most in-demand AI jobs. Other popular machine learning careers include data science and deep learning, robotics, AI, and NLP engineering, with excellent job prospects and development opportunities.
Starting an ML Engineering Career
Considering the immense machine learning job growth, the numerous career development opportunities, and the attractive salaries, starting a career in machine learning is a smart move.
Learning to excel in this demanding role is not easy, but we’re here to help. 365 Data Science is your gateway to the world of data, machine learning, and AI. Our training will help you acquire fundamental ML engineering skills—from statistics and mathematics to Python, ML, and DL techniques.
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