Artificial Intelligence (AI) has been around for a while, but recent and rapid developments in generative AI (GenAI) are making quite a splash around the world — and in the job market. We have seen an ever-growing surge in demand for AI-related roles over the last several years as businesses of all sizes and sectors look to leverage AI to improve their operations and gain a competitive edge. And with no signs of slowing down, this trend will likely become the norm, with more and more sophisticated AI developments.
And that’s where you come in! Yes, you! As AI becomes more intrinsic, businesses will need more people (like you) with the skills to develop, deploy, and maintain their systems. This creates huge opportunities for AI enthusiasts.
That’s why we’ve got a brand new GenAI game in The Arcade! Because the future is here and now is the perfect time to blast-off on your career in AI. Curious? Read on!
So what exactly does a career in AI entail? What are the most desirable (and available!) roles? And what skills does one need to succeed in this field? Let’s take a look!
1) Artificial Intelligence Engineer:
AI engineers are responsible for designing, developing, and deploying AI systems. They work with a variety of stakeholders to understand business needs, and then translate them into technical requirements. AI engineers also have a deep understanding of AI algorithms and machine learning techniques.
2) Data Scientist:
Data scientists are responsible for collecting, cleaning, and analyzing data. They use their analytical skills to identify patterns and trends in data, and then use those insights to make recommendations for business improvement. Data scientists also have a strong understanding of statistics and machine learning.
3) Machine Learning Engineer:
Machine learning engineers are responsible for building and maintaining machine learning models. They work with data scientists to collect and clean data, and then use that data to train machine learning models that can make predictions or decisions. Machine learning engineers also have a strong understanding of statistics and probability.
4) Robotics Engineer:
Robotics engineers design, develop, and build robots. They work with a variety of stakeholders to understand the needs of the robot, and then translate those needs into technical requirements. Robotics engineers also have a deep understanding of mechanical engineering, electrical engineering, and computer science.
5) Data Analyst:
Data analysts collect, clean, and analyze data. They use their analytical skills to identify patterns and trends in data, and then use those insights to make recommendations for business improvement. Data analysts do not typically have the same level of expertise in machine learning as data scientists, but they still play an important role in the AI ecosystem.
As you can see, there are many paths to success in an AI career, and demand continues to grow. A career in AI relies on a blend of technical prowess, analytical thinking, and creative innovation. The necessity for these attributes is amplified with ongoing developments in and the growing adoption of GenAI — which means we can also expect to see a rise in demand for other job roles such as AI ethics experts, AI systems managers, data annotation specialists, AI prompt engineers, AI-based fact checkers, and human-AI interaction specialists.
If you are interested in a career in AI, now is the time to start developing the skills you need to succeed by joining Arcade Level 3: GenAI and gaining hands-on experience with the tech that will shape the future.
