Artificial intelligence (AI) has been the most significant disruptive innovation in the 21st century. The hard knock of the technology is rocking the job sector as well. New jobs are being created while so many jobs traditional jobs are facing extinction.
The applications of AI are stupendous and showing once unimaginable vistas--self-driving cars, automated diagnosis in hospitals, and robotic assistants in malls. These are dream-like spectacles of the early days of the expanding AI revolution.
Careers in artificial intelligence are cropping up in a variety of settings. The AI jobs are up for grabs in companies, public organizations, education, government agencies, arts, healthcare, and in the military too.
In fact, many AI positions now need security clearance before hiring as they involve sensitive information.
AI is making inroads everywhere. But some industries will see more of its applications.
The World Economic Forum has said AI may lead to a net increase of 58 million jobs globally. Senior AI professionals report a skills gap in the recruitment of new scientists as a talent crisis according to an Ernst & Young report.
Artificial Intelligence jobs will also see an increase in the following fields.
The demand for talented engineers is considerable as they are the key operators to handle new opportunities in the cutting-edge area of AI research and development.
AI is the new catalyst that will impart efficiency in many sectors with high-value services.
Some popular job roles in the AI industry include the following.
AI Engineer: The responsibilities of an AI/Machine Learning developer are statistical analysis, deep learning systems, development of machine learning programs, implementing AI/ML algorithms, and training ML systems using data sets. The frameworks they operate will include Apache Hadoop, Spark MLib, Apache Signa. Azure ML Studio, Scikit Learn, Amazon Machine Learning, etc.
Data Scientist: A data scientist works with data engineers to automate and analyze data collection processes, massive data in order to trace out trends and find patterns, build predictive models and appropriate ML systems, strategies for decision-makers using compelling visualization tools and techniques. Tools used include R, SQL, Scala, SAS, Python, and SSAS.
AI has a high learning curve. Basic entry can be a bachelor's degree in computer science or a related discipline including Mathematics. But senior positions require a master's or Ph.D., degree. In basic hiring for AI roles, a college degree is not a hard requirement for companies like Apple and Google. They know success in AI roles depends on so many factors than a formal education document.
The AI career is a little different from other careers where a path is laid out. AI is still in its infancy and a candidate in the sector has to find his way ahead by being highly creative.
Universities may not offer prescribed courses with a major or specialization in AI. But there are many dedicated AI programs with unique approaches to opening career entry.
One starting point is computer science coursework and having a fair grip on data science, machine learning, and Java. Many undergraduate and graduate programs are sprouting with AI jobs in perspective.
AI overlaps many disciplines and has statistical methods as a bigger background. Taking interdisciplinary courses in cognitive science can provide the framework for AI applications.
Once the fundamentals are captured, AI subfields need to be taken care of. Many courses target specific applications in healthcare, biology, and neuroscience.
Carnegie Mellon, Stanford, and MIT have launched tracks for work in AI as supplemental programs and are useful to switch over for jobs in AI.
Microsoft’s AI track is Microsoft Professional Program covering the developer-focused AI School. The online program imparts job-ready skills to engineers to improve skills in AI and data science with guidance from hands-on labs and expert instructors. Google, MIT, Stanford, CalTech, and the University of Cambridge are running Machine learning courses.
For a career in AI and ML, certain skill sets are indispensable such as the following.
Statistical Skill: For AI aspirants, an in-depth understanding of statistics and probabilities is a must to analyze complex algorithms. Most of the AI models have patterns comprising large amounts of information and only statistical methods can unlock insights about the data.
Mathematical skills: Mathematical and probability skills are vital as AI features so many mathematical concepts to create artificial intelligence tools. Probability determines many outcomes and calls for its deeper understanding integral to superb AI models.
Programming skills: Artificial Intelligence career aspirants needs exemplary knowledge of programming languages such as Java, C++, Python, and R core.
Signal processing: In machine learning, feature extraction is important to understand model deployments. That is why artificial intelligence and machine learning engineers are expected to have advanced knowledge about signal processing techniques.
Distributed Computing: Since AI jobs face tackling vast chunks of complex data across data clusters, the aspirants need exemplary distributed computing skills. They must have expertise in applications including MongoDB and be sure to operate in cloud environments.
Continuous upskilling: The only way to gain experience is by looking for projects that give hands-on experience and join hands with other aspirants to upskill and stay tuned to industry requirements. Theoretical knowledge needs to be tested in the real environment by applying skills to practical applications.
Artificial intelligence (AI) will have a fundamental impact on the global labour market, business models and at the micro-level, it will be felt on working time, remuneration, and the working environment too.
To conclude, artificial intelligence is here to stay despite joy and concerns. It will attract the best talent as a lucrative field with high job growth. But the sector is too competitive.
Roles are niche. Therefore, advanced technical background and wider hands-on experience are essential to sustain. Those with this rare blend can shine and ascend to top roles in AI as the landscape is evolving fast.