Machine Learning Engineer
Machine Learning Engineer
Machine Learning refers to algorithms that find and apply patterns in data, and machine learning algorithms are behind most of the advancements you might hear about in artificial intelligence. Data is digitally recorded and stored continuously, and machine learning algorithms are capable of using statistics to find patterns in massive amounts of data, which is incredibly valuable.
Machine learning powers many services we use on a daily basis, from video streams like Netflix and YouTube to social media like Facebook. The data acquired from machine learning algorithms are so powerful that Machine Learning Engineers are in great demand, across industries and sectors because they bridge the gaps between aggregate data and turning this into tangible tasks for an organisation to learn, grow and act upon.
Machine Learning Engineers combine cutting-edge aspects of data analysis and software engineering to enable machines to learn without the need for further programming, working in a specific area of artificial intelligence so allow machines to take actions without being directed. End system examples of machine learning and the work of a Machine Learning Engineer include a self-driving car or a newsfeed customised to the individual user.
Machine Learning is incredibly broad, and there is some convergence with other disciplines like computational statistics, mathematical optimisation, data mining, exploratory data analysis and predictive analytics.
Unlike other areas of employment in software engineering and development, education for Machine Learning Engineers is very important. Many employers seeking a qualified Machine Learning Engineer will look for a relevant Masters degree or a PhD in an area of Machine Learning. Machine Learning is a relatively new field, and there are not many specialised courses available, so obtaining a relevant degree is very important, as it also reflects grounding in computer science fundamentals, data structures, algorithms, computability and complexity and computer architecture.
Machine Learning Engineer applicants should have good knowledge of Java, Python and C++, and will most likely be asked for evidence of commercial experience in computer programming. As a Machine Learning Engineer applying for a job, you’ll need to demonstrate job-specific skills like advanced mathematics, Python coding skills, Linuz SysAdmin skills, messaging like Kafka, RabbitMQ, distributed systems tools, competence with Infrastructure as Code (IaC) and more.
The demand for qualified Machine Learning Engineers continues to grow, and as a Machine Learning Engineer you could work across a range of sectors and industries, e.g. a large technology company, within the medical field, engineering or internet security. The limitless possibilities associated with Machine Learning give Machine Learning Engineers endless job security.
If you are a Machine Learning Engineer just starting out in your career, or you’re an industry veteran looking for a new opportunity, get in touch with one of our consultants today.
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