Introduction Because of rising demand in industries, artificial intelligence employment prospects have lately expanded. The notion that AI will produce a slew of new professions is accurate. A career in artificial intelligence looks to be more promising than any other employment accessible today. As a consequence, artificial intelligence is a profitable work prospect that will greatly assist hopefuls in advancing their careers. Nevertheless, before learning about the many AI occupations accessible, it is vital to first grasp what Artificial Intelligence is and what AI careers are available.
Artificial intelligence (AI) has opened up new possibilities for the future in recent years. It is making ripples throughout sectors, from space exploration to melanoma detection, making the unthinkable conceivable.
As a result, there has been a continuous increase in AI careers—LinkedIn lists AI practitioners as one of the 'jobs on the rise' in the last couple of years. In this article, we look at some of the best and highest-paying AI jobs available in 2023 and beyond.
Career Prospects in Artificial Intelligence Below are a few career opportunities to avail if you are pursuing or have pursued Artificial Intelligence:
Machine Learning Engineer - Machine learning engineers work at the crossroads of software development and data research. They use big data technologies and programming frameworks to build production-ready scalable data science models capable of handling terabytes of real-time data. Machine learning engineer positions are ideally suited to those with a background in data science, applied research, and software engineering. Strong mathematics abilities, experience in machine learning, deep learning, neural networks, and cloud applications, and programming skills in Java, Python, and Scala are required for AI positions. It also helps to be familiar with software development IDE tools such as Eclipse and IntelliJ.
In the United States, the average compensation for a machine learning engineer is $1,31,000. Companies such as Apple, Facebook, and Twitter pay substantially more—in the $170,000 to $200,000 level.
Research Scientist - One of the most academically motivated AI occupations is that of a research scientist. They pose novel and imaginative queries for AI to solve. They are specialists in a variety of artificial intelligence areas, including mathematics, machine learning, deep learning, and statistics. Researchers, like data scientists, are expected to hold a doctorate in computer science. Hiring managers require research scientists to be well-versed in computer perception, graphical modelling, reinforcement learning, and natural language processing. Benchmarking, parallel computing, distributed computing, machine learning, and artificial intelligence knowledge are advantageous.
Researchers are in high demand, with an average income of $99,800.
Data Scientist - Data scientists collect data, analyse it, and derive insights for a variety of objectives. They extract information from data and uncover significant patterns using different technological tools, procedures, and algorithms. This can range from as simple as spotting abnormalities in time-series data to as complicated as forecasting future occurrences and offering suggestions. A data scientist is required to have the following key qualifications:
A master's degree in statistics, mathematics, or computer science, for example. Unstructured data comprehension and statistical analysis Knowledge of cloud tools such as Amazon S3 and the Hadoop platform Programming abilities in Python, Perl, Scala, SQL, and other languages. Working understanding of Hive, Hadoop, MapReduce, Pig, Spark, and other similar technologies.
A data scientist's annual compensation is $105,000. A director of data science role may earn up to $200,000 with expertise.
Big Data Engineer/Architect - Big data engineers and architects create ecosystems that allow diverse business sectors and technology to efficiently connect. This profession might feel more extensive than data scientists since big data engineers and architects are often entrusted with planning, creating, and implementing big data environments on Hadoop and Spark platforms.
Most employers prefer candidates who have a Ph.D. in mathematics, computer science, or a related discipline. Yet, because this is a more practical job than, for example, that of a research scientist, hands-on experience is sometimes regarded as a viable alternative for a lack of academic degrees. Big data engineers are expected to be proficient in C++, Java, Python, or Scala programming. They should also have knowledge in data mining, data visualisation, and data transfer.
With an average compensation of $151,300, big data engineers are among the highest-paid professions in artificial intelligence.
NLP Engineer - Natural Language Processing (NLP) engineers are artificial intelligence (AI) specialists who specialise on human language, encompassing both spoken and written information. NLP technology is used by engineers who work on voice assistants, speech recognition, document processing, and so on. Organisations require an NLP engineer to have a specialist degree in computational linguistics. These may also be open to candidates with degrees in computer science, mathematics, or statistics. An NLP engineer would need expertise in semantic extraction techniques, data structures, modelling, n-grams, a bag of words, sentiment analysis, and so on, in addition to general statistical analysis and computer skills. Proficiency with Python, ElasticSearch, web development, and other programming languages may be advantageous.
An NLP engineer's starting compensation is $78,000, rising to more than $100,000 with expertise.
Business Intelligence Developer - Developers of business intelligence (BI) analyse complicated internal and external data to find patterns. For example, in a financial services firm, this may be someone who monitors stock market data to aid in investing decisions. This might be someone analysing sales patterns to inform distribution strategy in a product firm. Business intelligence developers, unlike data analysts, do not construct the reports themselves. They are often in charge of building, modelling, and managing complicated data in highly accessible cloud-based data platforms for usage by business users via dashboards. A BI developer should have the following qualifications:
A bachelor's degree in engineering, computer science, or a closely related discipline is required. Hands-on expertise in data warehouse architecture, data mining, SQL, and other related technologies. Knowledge of BI tools like Tableau, Power BI, and others. Technical and analytical abilities that are exceptional
Business intelligence developers make an average income of $86,500, with experience earning up to $130,000.
Conclusion LinkedIn has over 15,000 AI job listings in the current time. Hiring is taking place in a variety of businesses. The industry with the most available AI jobs appears to be technology, with businesses such as Apple, Microsoft, Google, Facebook, Adobe, IBM, Intel, and others looking for AI positions. Following closely after are consulting behemoths such as PWC, KPMG, Accenture, and others. Healthcare firms are increasingly hiring—GlaxoSmithKline now has many open AI-related opportunities. Retailers such as Walmart and Amazon, as well as media giants like Warner and Bloomberg, are all hiring. But, it is very important to firstly learn about the subject before applying it for professional purposes. In this situation, Skillslash has been in the ed-tech industry for a long time and is familiar with the requirements and desires of data science learners. <Data science course> The platform enables students to study from the greatest academics while also gaining project and real-world experience from IT leaders and top organisations. Courses such as Advance Data Science & AI, Full stack developer, Full stack Web Development, etc. may assist students in gaining a better understanding in sports and all other areas where they aim to thrive.