Artificial intelligence and machine learning are shaping our future more intensely than any other emerging technology this century. People who still haven’t heard about their popularity are likely to find themselves left behind, waking up in an environment full of technological innovations. The concepts of AI and machine learning have been present on the paper for years. They have come to life now because of the advancements in data storage and high computer processing power. You must have already seen applications powered by machine learning – driverless cars, facial recognition in smartphones, spam filtering, voice assistants, and Google Lens.
Machine learning is penetrating every industrial sector, and firms are reaping the many benefits associated with it. Aviation, healthcare, information technology, eCommerce, and manufacturing are some of the important industrial sectors that have seen rising innovations because of machine learning. For a layman, machine learning can be thought of as the magical phenomenon of making machines capable of learning on their own and performing human-like actions. It can predict future trends as long as they don’t deviate significantly from past trends. The more input data is given to the machines, the better it becomes to make decisions and provide accurate outcomes.
The growing popularity of machine learning has translated into many professionals seeking ways to learn this technology and start a career in AI. Today, you will find a lot of online courses that help you gain expertise in machine learning and become job-ready. The best part is that a learner looking for a machine learning course in London can take an online course designed in any country and learn from subject matter experts. But before you decide to learn machine learning, it’s important that you are familiar with the job roles available in this field. When you know about the possible careers in machine learning, you can better plan on what skills do you actually need for a desired career option.
This article introduces you to some of the top job roles associated with machine learning and what tasks they handle in an organization.
Top Job Roles in Machine Learning
The fact that you will have a promising career ahead in the field of machine learning is beyond question. Professionals skilled in machine learning are in high demand and command high salary packages across the world. If you too want to become a part of the machine learning talent pool, here are the job roles you should be aware of.
Machine Learning Engineer
As a machine learning engineer, your primary task would be to create computer programs and algorithms that allow machines to take actions without human intervention. They are involved in using big data tools and programming frameworks to create data science models that are ready to scale. They have good mathematical skills to perform computations and produce project outcomes and check the issues that need to be solved and try to make the algorithms more effective. They can also design effective ML algorithms for speech recognition, gaining customer insights, risk management, as well as fraud detection.
Data scientists are the professionals relied upon by companies to collect, analyze, and derive valuable information from the data so as to solve a specific business problem. They emphasize statistical analysis and research to identify which machine learning approach would best suit a given scenario and then model the algorithm and prototype it for testing. They know how to ask the right questions so as to begin the discovery process, make the data ready for analysis, and apply data science techniques like statistical modeling and machine learning.
Companies like Google, Amazon, IBM, and Microsoft are investing hugely in machine learning research and development initiatives. Being an AI/ML researcher, you can help such companies identify new product development opportunities. Their major responsibility is to research and develop new ML methods, approaches, and prototype systems. They conceptualize and explore innovative ways of leveraging data by building new ML algorithms and ask new questions that can be answered using machine learning. They lead Machine Learning development and experimental projects with the purpose of extending the existing ML capabilities.
Natural Language Processing (NLP) is an important subfield of AI that focuses on making computer systems capable of comprehending, manipulating, and analyzing natural human language. Basically, NLP scientists are expected to develop and design language understanding systems and effectively use text representation techniques to transform natural language into useful features. They define suitable datasets for language learning and build NLP systems according to client requirements. They are skilled in machine learning and implement appropriate ML algorithms and tools for NLP tasks.
Computer Vision Engineer
Computer vision, another area of AI, relates to computers analyzing images to make some sort of sense to solve real-world problems. A computer vision engineer is, thus, hired by companies to research and implement machine learning primitives and apply computer vision research as per the client’s requirements. They build image analysis algorithms and deep learning architecture, and further develop platforms for image processing and visualization. Developing and debugging software for advanced computer vision and image classification systems is also one of their major tasks.
With so many options available, which machine learning role are you interested to take up?