.png){kind=logo}
- Insights
- Cryptocurrencies
- Stocks
- White Papers
- Industry
- Geography
- Insights
- Cryptocurrencies
- Stocks
- White Papers
- Industry
- Geography
Artificial Intelligence, AI is undoubtedly the most in-demand and sought-after technology. The increasing popularity of AI has definitely turned the world upside down and for the better. The high paying AI jobs are definitely a reason that people are so fascinated by them. The article lists top 10 highly paying AI jobs to apply for in December 2022. These are the exact AI jobs to apply for a whooping salary.
You will be working with very large and complicated datasets as a data scientist. Both machine learning and predictive analytics will be used in this process. Additionally, you will need to be able to develop algorithms that allow for the collection and cleaning of such a large amount of data in order to prepare it for analysis. Starting out as a data scientist, your starting pay will be between 8 and 10 LPA, with more potential to increase your pay as you advance in your career.
As a research scientist, one of the most sought-after positions in the field of artificial intelligence, you will need to be knowledgeable in a variety of AI fields, including computational statistics, machine learning, deep learning, and applied mathematics. You must have substantial knowledge of graphical models, reinforcement learning, natural language processing, and graphical models in order to be hired for this position.
Research scientists are supposed to have advanced degrees, such as master's or higher, just like data scientists. However, many employers are not strict about this requirement and would take any advanced degree in a relevant topic.
Big Data Engineers or Architects have some of the top paying professions in the artificial intelligence sector, with starting salaries ranging between 12 to 16 LPA and plenty of room for advancement as they advance in their careers. It is preferable that applicants for this position already possess a Ph.D. in computer science or mathematics due to the fact that it is one of the highest on the ladder and entails more rigid facilitation than participation (or a related field).
Another of the most sought-after AI positions right now is data analyst. Since the advent of artificial intelligence, the work of data analysts has changed because they are no longer required to carry out tedious duties like processing or analysing data in order to get insightful information. Today, a data analyst's primary responsibility is to prepare data for machine learning models, then use the output to create useful reports. You need to have appropriate expertise with SQL, Python, and other important database languages in order to become a data analyst. Additionally, each data analyst must have knowledge of technologies for displaying data, such Tableau and PowerBI.
The majority of work on developing software products for AI applications is done by software engineers. They must constantly stay abreast of the most recent advancements in artificial intelligence technology in order to assist data scientists and software architects in creating and maintaining various helpful software. Additionally, software engineers do a number of highly important tasks like managing APIs, writing code, and quality control, among others. You require a formal degree in engineering, physics, mathematics, computer science, or statistics if you want to work as a software engineer. A further advantage is the possibility of receiving certification in any artificial intelligence course. The best programmers and analysts are also expected to be software engineers.
Software developers and data scientists come together to form the field of machine learning engineering. They use big data technologies and programming frameworks to develop data science models that are production-ready, scalable, and capable of handling terabytes of real-time data.
The ideal candidates for machine learning engineer positions have backgrounds in data science, applied research, and software engineering.
Candidates for AI positions should have a solid background in mathematics, familiarity with deep learning, neural networks, cloud applications, and Java, Python, and Scala programming.
Understanding software development IDE tools like Eclipse is also beneficial.
To find trends, business intelligence (BI) developers analyse intricate internal and external data. For instance, in a business that provides financial services, this could be someone who keeps track of stock market statistics to aid in investment selection. This might be someone who keeps an eye on sales patterns for a product company to help with distribution planning. Business intelligence developers don't really produce the reports, in contrast to a data analyst.
For business users to use dashboards, they are often in charge of designing, modelling, and maintaining complex data on highly accessible cloud-based data systems.
Software architects create and uphold technological standards, platforms, and tools. This is what AI software architects do for AI technology. They design and maintain the AI architecture, organise and carry out the solutions, select the tools, and make sure the data flow is seamless.
AI-driven businesses want at least a bachelor's degree in computer science, information systems, or software engineering from their software architects.
Experience plays just as much of a practical role as education.
You will be well-positioned if you have practical expertise with cloud platforms, data processes, software development, statistical analysis, etc.
When industrial robots began to gain popularity in the 1950s, the robotics engineer was possibly one of the first professions in artificial intelligence. Robotics has come a long way from the manufacturing lines to teaching English. Robotic assisted surgery is used in healthcare. Robotic humans are being created to serve as personal assistants. All of this and more is what a robotics engineer does. AI-powered robots are created and maintained by robotics engineers. Organizations often require graduate degrees in engineering, computer science, or a related field for these positions.
Robotics engineers may be required to have knowledge of CAD/CAM, 2D/3D vision systems, the Internet of Things (IoT), as well as machine learning and AI.
(NLP) engineers are experts in artificial intelligence (AI) who work with spoken and written human language. NLP technology is used by engineers who work on voice assistants, speech recognition, document processing, etc. Organizations require a specific degree in computational linguistics for the position of an NLP engineer. They might also be open to hiring candidates who have a background in computer science, math, or statistics. An NLP engineer would require expertise in sentiment analysis, n-grams, modelling, general statistical analysis, computer capabilities, data structures, modelling, and sentiment analysis, among other things.
It might be advantageous to have prior knowledge of Python, ElasticSearch, web development, etc.
