There has been gloom about AI lately and many people unfamiliar with the details of the matter think that it will replace human jobs and tech experts would be left jobless. But in reality, several people aren’t very accommodating of AI because they worry that AI automation will steal and destroy their jobs. Fortunately for all of us, the truth is that artificial intelligence creates a whole lot of jobs and opens up many avenues.
As long as a sense of threat continues to loom over the rise of Artificial Intelligence, and AI Tools such as ChatGPT, these tools also have the potential to create jobs with high salaries. As per reports, with the rise of AI, the role of prompt engineers has emerged, with a salary as high as you can get in any field.
The tech industry is always known for creating high-paying jobs, but usually for those who emerge from a STEM background. However, with the rise of ChatGPT and its various mods such as GPT 4, a new field of prompt engineers has been created.
As per a report by Bloomberg, the prompt engineer is a new role that has emerged all thanks to the rise of AI tools. These jobs also have the potential to pay as high as $335,000.
The jobs that are going to be hugely in demand due to Artificial intelligence are:
Data Sourcing
Data sourcing involves collecting and classifying data from various internal and external sources. These data sources are the origin points for all the data that you need. It may be a database, file, or API. Data sourcing gives you access to innumerable data that is like gold in today’s data-driven world.
Not all documents are the same. Even after the AI model has been adequately trained with different datasets for AI automation, there may be errors or doubts in classifying certain documents. In such circumstances, data sourcing specialists provide feedback and help enhance the performance of the AI model.
Data Detective
If you enjoy CSI or Sherlock a career as a Data Detective might be exactly what you are looking for. You can start with providing video annotation services where you will need to label all of the objects in each frame which the machine learning algorithms will use to recognize clues, evidence, and suspects.
You can then graduate to more advanced positions involved in using AI to analyze data and using it to narrow down the list of suspects. The use of artificial intelligence in law enforcement is starting to become popular and this creates a lot of jobs for creative and forward-thinking individuals.
Data Annotation Specialist
Have you ever wondered how machine learning algorithms are getting smarter and smarter? The reason is that tons of annotated data are being fed into the system so they can learn to recognize everything that is around them.
This involves taking raw data and annotating everything that you would like the machines to recognize. Regardless of whether you need video annotation or any other form of annotation, there is an increasing need for people who can provide these forms of services.
One of the main reasons that this job is so in demand is that it requires a lot of attention to detail, but it is very time-consuming. Developing machine learning algorithms requires a lot of time and effort by itself and companies simply do not have time to annotate the vast amount of images or videos that are required.
This is where the data annotation specialists come in. They play an important role in the project because if they do not label the data properly, the entire project will be delayed and you will have to go back to square one. Mindy Support has the experience and expertise to handle even the most sizeable data annotation projects. Regardless of the complexity or difficulties of the job, we will be able to get everything annotated within the specified time frame.
DEVOPS
Today, you can integrate machine learning and AI automation into any process or product to deliver better results. You can use AI and ML in manufacturing and retail, or you can integrate them with a camera to detect vehicles, assess the quality of food, and a whole lot more.
With so many integrations into different processes from all sectors, AI automation has opened up many avenues in DevOps, AIOps, and MLOps, instead of just ITOps.
These avenues require experts who can set up the AI/ML infrastructure and deploy its models, manage and maintain the model and logistics, and improve it for better efficiency.
The scope is also high in our mobile-first world, where around 97% of mobile users use AI-powered, voice assistants. These assistants heavily rely on ML models, thus creating opportunities in Dev/AI/ML Ops.
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