Artificial intelligence and machine learning are driving transformations in almost every industry. While there have been some concerns about artificial intelligence replacing jobs in nearly every sector, the hiring trends in AI itself have been overlooked. A report by BBC states that AI will replace as many jobs it will create. The demand for individuals with AI skills like deep learning and machine learning is not just limited to Silicon Valley but is actively sought after in almost every industrial sector.
According to the Inaugural AI Index by the Stanford University, the number of AI startups have increased 14 times their number in 2000 with the number of jobs requiring AI skills having grown 4.5 times since 2013.
Undoubtedly, artificial intelligence is an excellent career option for anyone who ’s interested in the field. Many artificial intelligence courses are making engineers competent to take up the following high paying job roles in the field:
Big data architect
Data architects are responsible for building a data eco-system that allows AI application systems to interact with each other and collect relevant data. The role requires a hands-on experience of working with large datasets, as big data architects are the contact persons for planning, designing, and developing the entire data management and interaction structure. Big data architects are expected to be proficient in software development languages like Scala, Java, C++, Python.
Big data architects are experts in working with Hadoop and Spark, and are experienced with working in data migration, data visualisation, and data mining projects While many big data architects and engineers work in these position directly after completing a PhD, a degree in computer science, maths, or related stream with relevant work experience is also shown preference.
The area of responsibilities of an AI researcher is concerned with researching AI trends and then developing new and interactive AI and machine learning algorithms. Their scope of work mostly relates to the research and development division of organisations. Not just limited to applying their findings to practical applications, they are published in research and industry journals as well. The role of an AI researcher can be for a variety of different fields, Internet of Things (IoT), advanced robotics, autonomous vehicles, to name a few.
Considering that most of the work of an AI researcher is centred around developing innovations in AI, having an expert understanding and knowledge of artificial intelligence, machine learning, and data science is a prerequisite. The role also requires an understanding of basic software development coupled with critical thinking, research skills, documenting and reporting. AI researches usually have a PhD in computer science and machine learning. Apart from this, work experience in publication and research is most sought-after.
DevOps is concerned with the unification of operations and development to improve the overall efficiency of the AI application being designed. This is performed through the practices of collaboration, integration, and automation. DevOps architects are responsible for developing, building, and maintaining an automated environment for several application development functions to operate with congruency. DevOps architects should be experts in tools of infrastructure automation like Chef, Puppet, Ansible, and SaltShack. They should also be proficient in Continuous Delivery (CD) and Continuous Integration (CI) tools like Jenkins and CruiseControl.
Since they design environments, DevOps architects need to have an understanding of multiple languages like Python, R, and Ruby. Along with excellent communication skills, they also need to be skilled at working with Kubernetes, Docker, and Containers. When it comes to educational qualifications, a post-graduate degree such as a Masters or PhD in computer science or a related field is a prerequisite. The role of DevOps architect is not an entry-level job and requires a minimum work experience of five years in developing high-performance big data and AI platforms.
A data scientist’s role deals with the analyses and interpretation of complex data that can aid an organisation to make informed business decisions. Data scientists develop and work on algorithms that allow them to collect, sort, manipulate, and analyse data that can later be fed into artificial intelligence algorithms. This role requires proficiency in software development using languages like R, Python, and C++, an insightful understanding of statistics, and expert practice in machine learning techniques.
Data scientists can be engineers with a masters in computer science, but given the complexity and high demand of this role, a PhD in computer science, maths, or a relevant field is more suitable. The role is not an entry-level job and requires at least two years of work experience with statistical and machine learning techniques.
Machine learning engineer
A subset of artificial intelligence, machine learning engineers, are mainly responsible for developing and managing platforms for implementing machine learning algorithms and projects. They are at the centre of AI project development, and usually, have a working and educational background in the fields of data science applied research, and coding.
Machine learning engineers should typically be experts in machine learning, neural networks, and deep learning with strong software development skills in multiple languages like Python, R, and C++. They should be able to understand the application of machine learning algorithms easily. When it comes to educational qualifications, a masters in computer science or a similar post-graduate degree is the only prerequisite.
There is no dearth of attractive and well-paying job roles in the artificial intelligence industry. As innovations keep driving the change, the demand for professionals having relevant skills is growing exponentially. So, for those with the necessary skills, artificial intelligence offers a lucrative career opportunity.
Salman is a prolific environmental writer, and has authored more than 300 articles in reputed journals, magazines and websites. He is proactively engaged in creating mass awareness on renewable energy, waste management, sustainability and conservation all over the world.
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