'Making it' in AI
Making a career in AI - what you need to know
This month we have been concentrating on automation, with a particular focus on career skills.
Jobs in automation and artificial intelligence (AI) are already highly evolved, with ‘AI Architect’ considered one of the most coveted jobs of the future.
In order to up-skill and develop a career in AI and automation you will need a comprehension of the various levels of expertise within AI.
Within the broad AI universe there are a variety of roles at differing levels, at the foundation you have data architects, then software engineers, and finally at the top of the tree you will find machine and deep learning engineers.
Moving on up another level beyond that top tier is where the research engineers are positioned, with high level skills in computer vision, language and speech.
A great many generic software engineers are actively seeking to up-skill in to the realm of AI and machine learning by evolving to become machine-learning engineers.
The intersection between systems and human behaviour is a fascinating space. If people are going to spend so much of their lives at work, it should be the place where their hearts, minds and souls come alive.
There are a vast number of jobs roles that will come into being, going beyond presently defined roles such as automation specialists and data scientists.
The skills dearth
As AI is a new career stream, there aren’t innumerate numbers of PhD graduates lined up for the vacancies that are being created.
Data engineers or software engineers can upskill fairly easily with online courses that are available, but for those considering advanced machine learning or deep learning, it becomes more difficult.
The majority of experienced product engineers don’t possess the mathematical or research skills required to support advanced AI roles. Conversely those with an academic and research background wont possess advanced production experience. The talent dearth for AI sits within the chasm between these two areas.
Gaining the education that you will need to pursue a career in AI is getting easier to enlist on. Online, there are number of options available for those who want to enter a career in AI and Machine Learning.
For those engineers and statisticians looking to move in to the field of AI there is more than one road that can be taken to reach their destination.
Certain areas of AI will require different levels of mathematics, computer science, robotics, engineering and analytical science theory. It is important to take your time to research the trends happening in your specialist area, from which you can identify the sorts of skills and expertise that you need to focus your directed learning on.
With a diverse and mixed array of industries you can work in if you desire a job working in AI, and they are not all exclusively centred with the technology or engineering sectors.
AI is rapidly evolving to become an important stand-alone discipline, which will present many opportunities and diverse career paths to those students equal to the challenge.