We are living in technological revolution era. Artificial intelligence is affecting not only our daily lives, but also the job market. Professions known for years are changing, becoming automated, but thousands of new professional opportunities are also being created. This is the era of building AI – 2023 was a landmark year for AI. Thanks to the implementation of ChatGPT and its growing popularity, the concept of AI has is not an abstract anymore; more and more people have started using it making everyday tasks at work and in private life easier and taking less time.
Together with developing technology areas such as security and management need to keep up. In 2024, we are concentrating on data integrity, security and privacy. There is big demand for AI specialists. Individual AI models are expected to face an intense growth as AI strives to become more versatile and helpful. On the other hand, they will also simultaneously shrink to focus on a specific specialty.
AI processing is moving from giant GPU farms to desktops and mobile devices. Intel, AMD and Qualcomm are developing new technologies – working on AI accelerators for desktops and laptops. Undoubtedly, cell phones will also soon use artificial intelligence. After the Internet, smartphones and mobile networks, which have already irreversibly changed our lives, the time has come for AI – working with AI is our new reality. Maybe the time has come to start your new job in AI and a new career path. Average salaries in AI field are higher than in many industries.
Skills required to work with Artificial Intelligence in 2024
The development of AI obviously means new AI career possibilities and new top AI jobs. The demand for artificial intelligence developers continues to grow. However, being a successful AI programmer means you need more than just coding skills. Proficiency in basic programming languages such as Python, Java and R is definitely essential, but also new languages, for example, Julia or Scala are necessary. The ability to model and engineer data in order to structure and preprocess it for efficient AI training and analysis is required. In addition to programming skills, the job requires machine learning techniques understanding and knowledge of various algorithms, model architectures and optimization techniques.
An effective AI and ML development position also requires knowing libraries and frameworks such as TensorFlow, PyTorch, scikit-learn and scikit-image, in addition to programming skills solid background in mathematics and statistics. Moreover, critical thinking, problem solving and analyzing user input play a key role. Mathematical skills, in turn, can be useful in developing advanced algorithms for programs.
In addition to technical knowledge and skills, working with AI also requires some knowledge of psychology. To create and train AI models specialist need to understand how others think might behave in various situations. After all, as we know, AI simulates human behavior. It is impossible to forget about AI security, privacy and data integrity. Those responsible for AI and ML development must know and follow best practices in security and ethics.
Jobs in AI in different industries
According to research, artificial intelligence development and application has an impact on labor productivity and can lead to a 1.5 percentage point increase in productivity over 10 years. Of course, some industries are clearly leading the way in implementing new technologies and AI systems. Technology, finance, healthcare, retail, manufacturing and cybersecurity are those areas where many skilled professionals have already have their new jobs. In the coming years, they will contribute to further development with forward-looking technologies.
Tech companies from all over the world are trying to stay on top of the news and are adding AI to their products. They want not only to increase their use, but also to make them simpler and more user-friendly. Google, Amazon or Microsoft are now actively hiring machine learning, data analysis and AI specialists to create services using the latest innovations. Another example of a leading industry is the financial sector. Here, artificial intelligence is being applied both in simple tasks such as automation and in more advanced ones – improving risk management and making better investment decisions.
Artificial intelligence is being implemented at all levels in the healthcare industry. Automation is used on the low end, to avoid human error, in billing and records management, but also on the high end, for early detection of serious diseases. AI is able to spot signs of cancer, for example, that humans may miss. Increasing operational efficiency is a goal the retail industry has set for itself. Here, AI solutions have been used to effectively manage inventory, prevent losses, detect trends, track customers’ personal shopping experiences and prevent fraud by finding suspicious spending patterns or transactions.
10 Top AI jobs
Many workers are justifiably concerned about losing their jobs due to the expansion of machine learning algorithms. But let’s not forget that this rapidly growing field is also creating new career prospects. Top AI jobs are changing at a rapid pace. According to the predictions of recruiters and labor market specialists, specialists are more sought after than generalists in 2024, but still generalists, developers and data science specialists are also still in high demand. Lets discover the top 10 jobs related to AI.
Careers in AI: AI product manager, AI research scientist and AI ethics specialist
Among the top AI jobs is AI product manager, whose job, like that of a program manager, is to develop and launch a product. In this case, of course, it’s an AI product, but the position is actually not much different from the others in terms of leading teams, planning and achieving milestones. Tech requirements to become an AI product manager are higher than most product manager positions. This is because an AI product manager needs to know what goes into creating AI applications, including hardware, software languages, data sets and algorithms. AI application development is different from web application development, the differences are both in the app structure and its development process.
Computer scientists are sought after to research and develop new artificial intelligence algorithms and techniques. These AI professionals work on developing and testing new AI models and cooperate with other researchers. What is more, they publish scientific articles and take part in conferences. As you can see, programming is only part of their tasks. Self-taught and informally trained programmers are welcome in tech industry. They must have a good understanding of computer science, mathematics and statistics, and a university degree is generally required.
Another profession is AI ethics specialist. As we have already mentioned, the ethical use of data to generate models is a major issue of 2024. Therefore, there is a great need for dedicated specialists to ensure responsible development and implementation of AI. In some large companies, AI ethics committees are being formed, which include employees with different backgrounds and specialties, lawyers, engineers, ethicists, public representatives and business strategists. The AI ethics specialist’s job is to help develop guidelines for AI projects, ethically review them and report their findings to the AI ethics committee. Among the requirements for this position are the ability to think critically, communicate effectively as well as knowledge of AI regulations.
Cybersecurity analyst, computer vision engineer and data scientist
Another field of artificial intelligence usage is cyber security, intrusion detection. Specialists proficient in cyber security and the use of AI to detect intrusions, defend against cyber attacks are in high demand. There is a growing demand for engineers related to the development and use of artificial intelligence. First, computer vision engineers. They specialize in writing programs which use visual input sensors, algorithms and systems. These programs see the world around them and act accordingly. Examples of their use include self-driving and self-parking cars or facial recognition. The C++ and Python languages and visual sensors, such as Intel’s Mobileye, are used to create these types of programs. Among the examples are face recognition, gesture recognition or scenery understanding.
Another profession is the data scientist who collects, analyzes and interprets data to solve problems and make decisions in the organization. Data mining, big data and analytical tools are used in jobs in the field. Companies can improve sales and operations, make better decisions and create new services and products. A data engineer uses predictive modeling to forecast future events, such as customer churn, and data visualization to present findings. Some also use AI and machine learning to create tasks automating models.
Hiring AI engineers! Machine learning engineer, natural language processing engineer and robotics engineer
When it comes to use machine learning, an engineer (machine learning engineer) is responsible for developing and implementing training algorithms and machine learning models. Training is the challenging aspect of machine learning. It involves the top level of skill and training. Advanced mathematical and statistical skills are necessary, so most machine learning engineers and deep learning engineers have advanced degrees in computer science, mathematics or statistics. They often continue their training in certificate or graduate programs in machine learning, deep learning systems and neural networks.
On the other hand, a natural language processing (NLP) engineer is an AI engineer who develops algorithms and systems which understand and process natural human language. Search engines use keywords and gather information from large amounts of online data. This is the main difference between traditional search engines and generative artificial intelligence interfaces such as ChatGPT. Artificial intelligence, on the other hand, creates new content based on other examples and patterns, and responds to queries in a chat format. Like a machine learning engineer, an NLP engineer does not necessarily have to be a programmer. He needs to understand linguistics as much as programming. NLP projects involve machine translation, summarizing text, answering questions and context understanding.
Another one in AI roles is a robotics engineer. This is a programmer whose job is to design, develop and test software to run and operate robots. Robotics has advanced significantly in recent years, with examples including automated household cleaning robots or precision equipment used in cancer surgery. Robotics engineers can also use their experience in artificial intelligence and machine learning to improve the performance of a robotic system. Robotics engineers typically design AI tools, software that makes little use of human assistance and instead relies on sensory data. So robotics engineers must debug software and hardware to ensure that all works as it should. They usually have an engineering education, e.g. master’s degree in electrical, electronic or mechanical engineering.
AI positions in healthcare
Finally, healthcare. Healthcare is an industry that perhaps like no other needs a bridge between technology and medical expertise. AI technologies designed for healthcare require hiring AI professionals. Artificial intelligence can help doctors and patients in many ways. It is also one of the most sensitive areas when it comes to securing private data.
Artificial intelligence offers many job opportunities and good salaries in healthcare. It helps doctors – diagnosing diseases and identifying the best treatment plans, helping them make critical medical decisions. Another example of the use of AI in healthcare is robotics – robots assisting in surgical procedures in the operating room. The use of AI in healthcare, of course, requires a thorough understanding of medical terms and terminology, as well as expertise in artificial intelligence.