One of the technological areas in the twenty-first century that is advancing the fastest and having the biggest impact is artificial intelligence (AI). Applications of AI are revolutionising a number of industries, including cybersecurity, healthcare, education, and finance. Because of this, there is a huge need for AI specialists, which is opening up fascinating new career paths for researchers, developers, engineers, and data scientists.
The top ten AI jobs for 2024 are as follows:
1. Machine Learning Engineer: This person is in charge of creating, designing, and implementing algorithms and systems that can learn from data and carry out various tasks such natural language processing, classification, recommendation, and prediction. A solid foundation in computer science, mathematics, statistics, and programming languages like Python, R, Java, or C++ is often required of a machine learning engineer.
2. Data Scientist: A data scientist uses a variety of tools and techniques, including statistical modelling, machine learning, data mining, and data visualisation, to gather, analyse, and understand big and complex datasets. According to Glassdoor, a data scientist normally possesses a solid foundation in mathematics, statistics, computer science, and programming languages like Python, R, SQL, or SAS.
3. AI Research Scientist: An AI research scientist is in charge of carrying out novel and creative research in a range of AI-related fields, including deep learning, reinforcement learning, computer vision, natural language processing, speech recognition, and explainable AI. A PhD or master’s degree in computer science, artificial intelligence, machine learning, or a similar discipline is usually required for an AI research scientist. They should also have published articles in respected publications or conferences.
4. AI Ethics Consultant: An AI ethics consultant is in charge of making sure that moral standards and ideals like justice, accountability, transparency, and privacy are upheld in the design and implementation of AI systems. An AI ethics consultant is someone who understands AI technology and their societal ramifications and typically has a degree in philosophy, law, sociology, psychology, or a similar subject.
5. Robotics Engineer: This person is in charge of creating, constructing, testing, and maintaining robots and robotic systems that can be used in a variety of industries, including healthcare, entertainment, manufacturing, and exploration. A robotics engineer is knowledgeable about robotics hardware, software, and algorithms and usually has experience in mechanical, electrical, computer, or related fields.
6. AI Product Manager: This person oversees all aspects of an AI product’s lifecycle, including conception, development, launch, and assessment. An AI product manager is someone who understands AI technology and their commercial potential and often has a background in business, marketing, or a similar discipline.
7. AI Solutions Architect: An AI solutions architect is in charge of creating, designing, and putting into practice AI solutions that are tailored to the particular demands and specifications of customers or organisations. A background in computer science, software engineering, or a similar discipline is usually required for AI solutions architects. They also have knowledge of AI technologies and how to integrate them with current platforms and systems.
8. Software Engineer: A software engineer is in charge of developing, testing, and maintaining software programmes that make use of artificial intelligence (AI) technologies, like speech recognition, computer vision, machine learning, and natural language processing. A software engineer usually possesses programming languages like Python, Java, C++, or C# and has a background in computer science, software engineering, or a similar discipline.
9. Data Analyst: A data analyst gathers, purges, and transforms data from multiple sources and uses that information to generate conclusions and suggestions. A data analyst usually possesses knowledge of data analysis tools and methodologies, such Excel, SQL, Tableau, or Power BI, and has a background in mathematics, statistics, computer science, or a similar subject.
10. Computer Vision Engineer: Creating and implementing computer vision algorithms and methods that let computers comprehend and analyse visual data, such photos, movies, or facial recognition, is the responsibility of a computer vision engineer. An expert in computer vision libraries and frameworks, such as OpenCV, TensorFlow, or PyTorch, plus a background in computer science, computer engineering, or a similar discipline are common qualifications for a computer vision engineer.
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