Getting a job in Artificial Intelligence or Machine Learning
If you want to work in the field of Artificial Intelligence (AI) or Machine Learning (ML) then naturally the first thing is to understand that these terms refer to software that has been designed to learn in a similar way to humans. Utilising speech recognition, language translation, auto pilot features and so on, AI systems are gaining prevalence in the modern world.
Before we tackle the ‘what’ of careers in AI, let’s look at the ‘who’. What type of person fits the mould for AI jobs? The best place to start is mathematics. Individuals wishing to join the ranks of AI professionals should have a strong maths background and a leaning towards science. The likes of statistics, algorithms, probability, physics, mechanics and cognitive learning theory all come into play when working in AI and ML.
The types of jobs you’ll be looking at within the realms of AI and ML comprise the theoretical and the practical. There are those who focus on research in a bid to uncover new types of systems and capabilities and work out new ways for machines to think in order to support real world situations. Then you have the programmers who spend their time developing algorithms to be used with the software created by engineers, developers and technicians. They create software and hardware needed for analysing data and making important decisions, as well as the equipment we use, from self-driving cars and military drones to Google Home and even special tools used by surgeons in operating theatres.
Working in AI and ML requires a high degree of technical aptitude, as within your realm of responsibility will be the maintenance and repairs of various technology and software programs. It is up to you to lend your logic and problem-solving abilities to devising cost-effective, efficient solutions for your business or organisation. And you must be constantly learning in order to stay ahead of the continually evolving AI landscape so that you are ready to predict the innovations in technology that will give way to high-end programs designed to give businesses the edge in their markets.
While your technical expertise is highly valuable, perhaps more so is your ability to convey your specialist knowledge to others across the industries you’re working in. You must be able to explain how they can implement AI tools and services in a way they can understand so that they can do their jobs effectively.
What’s important to understand about AI is that its key objective is not solely to replace the human component of an industry but to support industries by making the decision-making process easier. So, when you’re choosing where to pursue employment whether it’s with a private company, public organisation, education, the arts, healthcare, in a government department or the military; make sure to thoroughly read the job description to understand the specific qualifications you need for the role and industry you want to work in. For example, some may require knowledge of languages like Python or MatLab while AI jobs in the healthcare sector may require you to have used data services like Spark or Blockchain.
For those at entry level, it goes without saying to secure your grounding in maths and look into any and all courses you can in Machine Learning. You want to approach AI jobs with a strong foundation in computer and programming skills, knowledge of C++ and algorithms should be reinforced with general business acumen so that you can demonstrate an understanding of how your expertise will translate to real world feasibility.
Those with existing programming knowledge should be able to hit the ground running and start coding straight off the bat, while those candidates coming from a career in data analysis or data science will need to acquire programming skills as well as proficiency in model building and data visualisation.
Opportunities for AI professionals are buoyant, especially considering the deficit of trained AI and ML professionals in the current market. AI and ML professionals are software developers, data scientists, machine learning engineers, Python developers, engineering consultants, researchers and technicians so do your homework to discover which area of AI is best for you. Become a technology addict, read papers and case studies on AI and ML, robotics, automation and other sophisticated computer software and programs, and invest your personal time in experimenting with the likes of PostgreSQL, GraphQL, Ruby, Node.js and AWS.