Top 5 Artificial Intelligence (AI) in-demand Jobs for you today
The future looks promising for job opportunities in the field of artificial intelligence (AI), which is great news for individuals already working in this rapidly expanding domain. In fact, machine learning engineers and data scientists have consistently ranked at the top of Indeed’s list of Best Jobs for several consecutive years.
According to the US Bureau of Labor Statistics (BLS), careers in artificial intelligence are categorized alongside computer and information research scientists. The BLS predicts a remarkable 21 per cent job growth in the employment of computer and information research scientists from 2021 to 2031, a rate significantly above the national average.
Given the recent surge in AI technology, exemplified by innovations like ChatGPT, you might be contemplating a career in artificial intelligence. But what kinds of roles are available, and how can you secure a position in this field?
Allow us to guide you through the various AI job opportunities and their average salaries.
1. Artificial intelligence (AI) engineer – $120,017
AI engineers are skilled experts who harness the power of artificial intelligence (AI) and machine learning methodologies to craft applications and systems tailored to enhance the efficiency of organizations. The core essence of AI engineering lies in the creation of the essential tools, systems, and procedures that facilitate the practical application of AI to address real-world challenges.
In this dynamic field, algorithms are honed through a process of “training” using data, enabling them to acquire knowledge and continually improve their performance. The pivotal role played by AI engineers extends to cost reduction, heightened productivity, increased profitability, and the formulation of valuable business insights and recommendations.
2. Machine learning engineer – $125,087
Machine learning engineers play a pivotal role in the realm of artificial intelligence (AI). Their responsibilities encompass researching, constructing, and conceiving AI algorithms tailored for machine learning applications. Additionally, they are tasked with the maintenance and enhancement of pre-existing AI systems.
Notably, machine learning engineers frequently act as intermediaries within cross-functional data science teams, working closely with their counterparts, data scientists, who are responsible for crafting models fundamental to AI systems. Part of their core duties involves conducting experiments, executing tests, conducting thorough statistical analyses, and crafting intricate machine learning systems.
3. Data engineer – $115,592
Data engineers play a pivotal role in constructing systems designed to gather, oversee, and transform unprocessed data into valuable insights that can be readily interpreted by data scientists, business analysts, and other data experts. Their primary objective is to render data easily accessible, thereby enabling organizations to harness it for the purpose of assessing and enhancing their overall performance. Data engineering, as a discipline, possesses a wide-ranging scope with practical applications spanning virtually every sector and industry.
4. Robotics engineer – $101,062
Robotics engineers play a pivotal role in creating robotic solutions across diverse sectors such as automotive, manufacturing, defence, and healthcare. These skilled professionals are responsible for crafting novel products and constructing prototypes for rigorous testing. Some robotics engineers may work on-site within manufacturing facilities, supervising the production of robots, while others are engaged in real-world monitoring to assess their performance. The field of robotics engineering seamlessly merges mechanical and electrical engineering with computer science, forming a dynamic and multifaceted discipline.
5. Data scientist – $126,575
Data scientists play a crucial role in shaping the direction of organizations and teams by identifying the key inquiries that should be posed and devising strategies to address these queries through data analysis. Their work frequently involves constructing predictive models to speculate and predict trends and results. Additionally, data scientists frequently employ machine learning methods to enhance data quality or enhance the offerings of products or services.