In this digital age, businesses are hungry to integrate artificial intelligence (AI) into products and services. AI is the main driver of machine learning, which enables software programs to detect patterns and make logical decisions based on information. As a result, the role of Machine Learning Engineers has become increasingly business-critical. In this article, we’ll explore what it takes to become a machine learning engineer, what the job prospects look like and what skills you’ll need. 

What is machine learning?

A machine learning engineer builds self-running software that learns from data and automates predictive models. Machine learning engineers sit at the intersection of software engineering and data science, possessing skills from both disciplines because of the interdisciplinary nature of the job. Because of this, machine learning engineers are in high demand across all industries that rely on automation, big data, or making their systems and services more efficient. Due to the challenging nature of the role, and competition for top talent, finding and hiring Machine Learning Engineers can be challenging. Companies such as Datasearch consulting can help with this challenge. 

AI Basics

Artificial intelligence is the main driver behind machine learning, which is the ability of software programs to detect patterns and make logical decisions based on information. In order to become a machine learning engineer, you need to know the basics of AI, such as expert systems and neural networks. Expert systems are computer programs that emulate human decision-making, such as medical diagnosis. Neural networks are models inspired by the human brain in which data passes through nodes that simulate neurons. In order to become a machine learning engineer, you need to understand how each of these systems works in order to apply AI to your work.

What are the employment prospects for Machine Learning Engineers?

Data analytics, natural language processing, image recognition and other fields of AI are growing rapidly in demand. In fact, machine learning jobs have increased 75% over the past 4 years, and the growth is expected to continue. The US Bureau of Labor Statistics indicates that information and computer science research employment opportunities will increase at a faster rate than most other occupations, with a growth rate of 21 per cent up until 2031. Furthermore, the median annual income for these professions is significantly high, at $131,490. The job title “Machine Learning Engineer” was recognised as the number one job in the United States of America in 2019, according to Indeed. With a base pay of $146,085 and a remarkable increase of 344% in job postings.

LinkedIn showed over 114,000 job openings for Machine Learning, with salaries ranging from $123,000 to $178,000. Some examples of salary ranges at different companies include:

• Principal Machine Learning Scientist at Amazon, $123k to $178k 

• Machine Learning Engineer at TikTok, $104k to $225k

• Machine Learning/Deep Learning Engineer at the Toyota Research Institute $111k to $195k. 

The growth of job opportunities for machine learning engineers makes it a great career for prospective employees from various industries and backgrounds. 

Machine Learning Engineer Job Descriptions

A machine learning engineer programs a system or software to learn without human intervention. For example, a recommendation engine on YouTube or Netflix is able to detect spam or inappropriate content on its own. There are many different job descriptions for machine learning engineers, and they vary depending on the industry, organisation, and team. Typically, someone in this position must be able to design and train computers to learn autonomously.

Having expertise in both data science and software engineering is what makes this skill set stand out. By being too specific, Machine Learning Engineers’ job descriptions can self-eliminate prospective candidates, and therefore it’s important to remain as flexible as possible when writing job decisions. 

Skills and capabilities required for the role can include the following: 

• Proficiency with programming languages such as Python, SQL, and Java; 

• Hypothesis testing; data modelling; mathematical knowledge, probability and statistics (for example, Naive Bayes classifiers, conditional probabilities, likelihood, Bayes’ rule and Bayes nets, Hidden Markov Models, and dynamic programming), variance, correlations, and understanding of variance, and the ability to develop an evaluation procedure for predictive models and machine learning algorithms. 

• System design and data structures such as stacks, queues, graphs, trees, and multi-dimensional arrays are among the required skills in software engineering. 

• Computability, complexity, and approximate algorithms as well as computer architecture such as memory, clusters, bandwidth, deadlocks, and caches, are all included.

The Soft Skills Required for Machine Learning Engineers

As competition for roles increases, so does the need for prospective candidates to develop their soft skills in order to stand out. Ultimately, a Machine Learning Engineer will come in contact with a range of stakeholders, from users to customers, senior management to investors. Soft Skills that can help candidates stand out from the crowd include

1. Communication Skills: Communication is a key factor for any job role and plays a crucial role in various situations – from interviews to describing ML models to non-tech individuals and proposing projects to investors.

2. Being a Team Player: As a software engineer, it is imperative to stay connected with other developers and other non-technical staff, such as product designers, managers, testers, etc.

3. Time Management: In order to meet tight deadlines, it is important to set the correct amount of time for each task. Being an ML expert, it is wise to allot twice the amount of time than usual to make sure the pressure is manageable.

4. Being a Leader: After obtaining a good amount of experience in the ML field, it is essential to cultivate leadership qualities. Become a friend, mentor, encourager, and critical thinker. Adjust your role based on the needs of the moment. By taking the lead, you can accomplish the unachievable and make it all worthwhile.

5. Work Ethic: Adopting an ethical approach usually has a positive outcome. Establishing your work morality and following it strictly makes you a better professional. Discipline, motivation, aspiration, insight, efficiency, and hard work are the essential characteristics that help create a successful career.

Conclusion

Becoming a machine learning engineer can be challenging, but it’s a rewarding career path that allows you to apply many skills you already possess. In order to become a machine learning engineer, you need to develop a variety of skills that work together to support the field. You’ll need to understand the basics of artificial intelligence, have a strong foundation in programming languages, have a solid grasp of statistics, be skilled in data visualisation, have a working knowledge of database languages and have the ability to create and publish research papers. 

How Dataseach can help you

As a candidate

Finding Machine Learning Engineer roles isn’t difficult, but finding a recruitment partner that will put you in the best possible light in front of prospective employers can be a real challenge. At Datasearch, we work with you as a prospective employee to help you accentuate your skills in machine learning and show you the keys to success in the interview process for each and every client we work with. 

As a company

Currently, there is a real shortfall of Machine Learning Engineers available. At Datasearch we pride ourselves on being able to find the best possible candidates for you and present your company as their future employment destination. Remember, your next Machine Learning Engineer is already working at a company, competitor, or in a different industry, and we are here to help ensure that your business and job opportunity is presented to them in the most convincing way possible. Our role isn’t just about posting to job boards; it’s about building relationships. Visit our website, or contact us today at info@datasearchconsulting.com to see how we can help.