As Artificial Intelligence "AI" takes over businesses and services, new job titles are being created that involve AI, machine learning, vision, research and development, and data. Let’s take a look at today’s most popular AI jobs and the skills that each of them requires.
Machine learning engineer is first on the list with an annual salary of $142K. Machine learning engineers are expected to design and build machine learning systems that process and classify data. They are expected to work in projects that involve computer vision and natural language processing. They evaluate potential improvements, prototype and validate ideas, and productionize new strategies. Building and optimizing systems, tools, and validation strategies to support new features are among the job responsibilities. They should be able to use big data technologies to build data mining pipelines.
Next in the list is data scientist, with a salary of $141K. A data scientist’s role is to analyze and visualize data. They build and implement machine learning models to make decisions. They must be a mixture between a statistician, a scientist, a machine learning expert, and an engineer.
R&D engineers make an average of $140K. This requires experience in reading research papers and doing literature research. They spend a considerable amount of time conducting literature reviews and browsing through theoretical work before deciding which theories can be applied and transformed to real products. This is one of the most important jobs in the market as it is considered the new idea factory.
Business intelligence developers come next with an average salary of $136K. Responsible for creating and maintaining data models at the conceptual and logical levels, business intelligence developers are expected to work on data visualization tools to provide business insights regardless of the sector the business occupies.
Computer vision engineers come in fifth with a $135K annual salary on average. This is considered one of the most fun jobs in the AI field. Computer vision engineers focus on the research, analysis, and development of computer vision technologies that support the development of software components and tools. They must stay up-to-date in the scientific field and keep up with the latest technologies. The applications that computer vision engineers create can impact security and inspection systems, self-driving cars, and a variety of web and mobile applications. They use the most famous machine learning tools today, including TensorFlow, Caffe, Theano, Numpy, and Scikit. Most of those are Python libraries, so if you are interested in this field then Python is your starting point.
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The 6 most in-demand AI jobs
