Unquestionably, the most in-demand and sought-after technology is artificial intelligence, or AI. The world has undoubtedly changed for the better as AI becomes more and more prominent. The fact that AI jobs are so lucrative is undoubtedly why people are so captivated by them. The top 10 high-paying AI positions to apply for in December 2022 are listed in the article. Apply for these specific AI positions today for a fantastic compensation.
Data Analyst
As a data scientist, you will deal with incredibly vast and complex datasets. This technique will combine machine learning and predictive analytics. In order to gather and clean up such a massive amount of data in order to prepare it for analysis, you will also need to be able to create algorithms. Your beginning salary as a data scientist will range between 8 and 10 LPA, with greater room for growth as your career progresses.
Research Scientist
One of the most sought-after jobs in artificial intelligence is that of a research scientist, which requires expertise in a number of AI disciplines, including computational statistics, machine learning, deep learning, and applied mathematics. To be hired for this role, you must have in-depth understanding of graphical models, reinforcement learning, natural language processing, and graphical models.
Like data scientists, research scientists are expected to hold advanced degrees, such as master’s or above. Many firms, however, are lenient with this criteria and will accept any postgraduate degree in a pertinent field.
Engineer/Architect for Big Data
With beginning wages between 12 and 16 LPA and plenty of room for development as they advance in their careers, big data engineers or architects have some of the highest paying occupations in the artificial intelligence industry. Because this position is one of the highest on the ladder and requires more rigid facilitation than participation, it is preferred if applicants already have a Ph.D. in computer science or mathematics (or a related field).
Data Scientist
Data Scientistis one of the most in-demand AI jobs right now. The role of data analysts has altered since the development of artificial intelligence because they are no longer required to perform laborious tasks like processing or analysing data in order to obtain insightful information. Today, the main duty of a data analyst is to prepare data for machine learning models, then use the results to produce relevant reports. To become a data analyst, you must possess the necessary proficiency with SQL, Python, and other significant database languages. Each data analyst must also be familiar with technologies like Tableau and PowerBI for data visualisation.
Computer programmers
Software developers are responsible for the majority of the effort involved in creating software products for AI applications. To enable data scientists and software architects create and manage diverse useful applications, they must always stay up to date on the most recent developments in artificial intelligence technology. Software engineers perform a variety of other crucial jobs as well, including maintaining APIs, writing code, and quality control, among others. If you want to work as a software engineer, you must have a formal degree in engineering, physics, mathematics, computer science, or statistics. The potential for certification in any artificial intelligence course is an additional benefit. Software engineers are thought to be the greatest analyzers and programmers.
Engineer in Machine Learning
The discipline of machine learning engineering is formed by the collaboration of software engineers and data scientists. They create data science models that are production-ready, scalable, and able to handle terabytes of real-time data using big data technologies and programming frameworks.
Data science, applied research, and software engineering credentials are appropriate for machine learning engineer employment.
Candidates for AI positions should have a strong mathematical foundation, be knowledgeable with deep learning, neural networks, cloud applications, and programming in Java, Python, and Scala.
It’s also helpful to understand software development IDE tools like Eclipse.
Developer of business intelligence
Business intelligence (BI) developers examine complex internal and external data to identify trends. For instance, at a company that offers financial services, this might be a person who monitors stock market statistics to help with investment decision-making. For a product company, this might be someone who monitors sales trends to aid with distribution planning. In contrast to a data analyst, business intelligence developers don’t actually create the reports.
Business users are frequently in responsible of building, modelling, and managing complicated data on easily available cloud-based data platforms so that they may use dashboards.
Technology Standards, Platforms, and Tools are Developed and Maintained by Software Architects. AI software architects work in this field to develop AI technologies. They organise and implement the solutions, choose the tools, create and maintain the AI architecture, and ensure that the data flows smoothly.
For their software architects, AI-driven companies want at least a bachelor’s degree in computer science, information systems, or software engineering.
Both education and experience have practical value.
If you have practical experience with cloud platforms, data operations, software development, statistical analysis, etc., you will be in a good position.
Mechatronics Engineer
The robotics engineer was possibly one of the first jobs in artificial intelligence when industrial robots started to gain prominence in the 1950s. Robotics has advanced significantly from working on assembly lines to instructing English. In medicine, robotic surgery is practised. Humanoid robots are being developed as personal helpers. A robotics engineer accomplishes all of this and more. Robotics engineers design and maintain AI-powered robots. For these professions, organisations frequently require graduate degrees in engineering, computer science, or a similar subject.
Knowledge in CAD/CAM, 2D/3D vision systems, the Internet of Things (IoT), machine learning, and AI may be necessary for robotics engineers.
Engineers that specialise in natural language processing (NLP) for artificial intelligence (AI) deal with both spoken and written human language. Engineers who work on voice assistants, speech recognition, document processing, etc. use NLP technology. For the position of NLP engineer, organisations demand a particular degree in computational linguistics. They might also be willing to hire those with a background in math, statistics, or computer science. In addition to other skills, an NLP engineer would need to be knowledgeable in sentiment analysis, n-grams, modelling, general statistical analysis, computer skills, data structures, modelling, and sentiment analysis.
