Artificial intelligence (AI) will revolutionise our lives, and while AI may take some jobs, it will also create thousands of careers.
Thanks to the notoriety of ChatGPT, the concept of artificial intelligence is no longer some sort of abstract notion. While AI has been used quietly in the background on most social platforms, it is now accessible to everyone. From writing code to CVs and everything in between, people are using AI to make their lives easier.
Many tech visionaries believe AI will have the same impact as the internet, smartphones and the mobile web. Rather than taking a Luddite approach and writing off the benefits that AI can bring to life, now is the time to adopt the technology – including work.
Along with machine learning, artificial intelligence is one of the fastest-growing fields in technology, and there are plenty of exciting career opportunities for those looking to future-proof their career. There are predictions that AI will create 97 million new jobs by 2025 – and many businesses are struggling to find qualified people that can create, train and maintain AI and ML systems.
For those considering a career change, we’ve curated a handful of roles within AI that will be in high demand in the coming years. While these roles do require previous knowledge of computer science and maths, online courses and new certifications in the field are popping up just as quickly as tech advances.
So if you are thinking about reskilling yourself for a career in artificial intelligence, consider these exciting opportunities.
Many of us have interacted with chatbots on-line, and as generative AI and large language models continue to evolve, the chatbot is a perfect platform to share information. Chatbot developers use natural language processing, programming and other technologies to create chat functions that provide a human-like interaction with users – answering questions, providing recommendations, and other tasks instantly.
AI prompt engineer
The rapid growth of the AI industry is creating new job titles and opportunities, and the role of an AI prompt engineer is a perfect example. In this role, a prompt architect excels in crafting textual cues that resonate with expansive language models and generative AI tools. Diverging from conventional coders, AI prompt engineers harness the power of written language to scrutinize AI systems for quirks.
The responsibilities of an AI prompt engineer extend to the training and refinement of tools like OpenAI’s ChatGPT, Google’s Bard, and other cutting-edge AI platforms. The ultimate goal is to ensure these tools provide accurate and pertinent responses to inquiries from individuals.
Machine learning engineer
One of the most in-demand AI-related roles, a machine learning engineer is responsible for designing, building, and deploying machine learning models. You’ll be working with large datasets, developing algorithms, and optimising models for performance. A career as a machine learning engineer will earn you a high-paying role and job security.
AI ethics specialist
One of the biggest AI-related concerns many have is the bias that can be created due to human biases during programming. For that reason, an AI ethics specialist is key to AI’s impartiality. An AI ethics specialist is responsible for ensuring that AI-powered products and services are developed and used in an ethical and responsible way. This involves identifying potential ethical issues and developing guidelines and policies for AI development. Like all the other roles on this list, you’ll need some background in computer science, but you’ll also have a strong background in ethics and philosophy.
If you’re looking to break into the industry, getting into data science is a great way to kick off and future-proof a new career in AI. A data scientist analyses large amounts of data to uncover patterns and insights that inform business decisions. This involves using machine learning algorithms and statistical models to identify trends and make predictions. A strong background in statistics, mathematics, and computer science is typically required for this role.
With an average salary of £42k ($50k USD) per year and growing in demand, a career in AI research offers up a tremendous opportunity. An AI researcher is responsible for developing new algorithms and models for machine learning. This involves researching machine learning techniques, experimenting with different approaches and publishing the results.
Ever dream about actually working with robots? A robotics engineer is responsible for designing and building robots that can perform specific tasks. This involves integrating machine learning algorithms into the robot’s control system to enable it to learn and adapt to new situations. You’ll need a strong background in electrical and mechanical engineering, so it’s not the easiest career to get into, but it can be very rewarding as well as just being really cool.
Natural language processing (NLP) engineer
Without the input of natural language processing engineers, we would use our phones in a completely different way. An NLP engineer is responsible for developing algorithms and models for processing and analysing natural language data. This involves working with large datasets of text and speech, developing algorithms to analyse and classify the data, and optimising models for accuracy. A passion for languages and problem-solving skills are essential to become a successful NLP engineer.
Computer vision engineer
Truly one of the most ‘futuristic’ roles on our list, a computer vision engineer makes it easier for computers to ‘see’ images and videos. Also known as CV engineers – they develop algorithms and models for analyzing visual data. This involves working with large datasets of images and videos, developing algorithms to identify objects and patterns, and optimising models for accuracy.
AI product manager
Finally, who’s going to manage the life cycle of an AI project? An AI product manager is responsible for overseeing the development of AI-powered products and services. This involves identifying user needs, defining product requirements, and managing the development process. You’ll need a background in product management and a solid understanding of AI and machine learning to succeed in this role.
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