Artificial Intelligence (AI) technology has been gaining popularity in recent years. From robots serving food in restaurants to self-driving cars, these applications of artificial intelligence can be seen in our day-to-day lives. John McCarthy, an American computer scientist who coined the term artificial intelligence, defines this discipline as the science and engineering of making intelligent machines, especially intelligent computer programs. Mainly, AI develops intelligent software and systems based on how human minds think, learn, decide, and solve a problem. It enables machines to perform human-like functions by learning through experience.
While professionals across the globe are worried about robots replacing humans, a Gartner study reports that AI is an emerging field that will create 2.8 million jobs by 2020. AI is a broad term, encompassing general artificial intelligence, machine learning, expert systems, data mining, and more. In today’s world, AI capabilities are in high demand across industries—gaming, robotics, face recognition software, weaponry, speech recognition, vision recognition, expert systems, and search engines.
If you’re evaluating career options in this emerging field, look at these top five jobs in artificial intelligence and the skills that you’ll need to transition into these roles.
Read More: With an interest in R&D and Analytics, Nayan Panday wanted to learn Python and AI/ML to help him grow. Read more about his journey with our AI and ML Certification in his Simplilearn AI Course Review.
Top Artificial Intelligence Skills
Computer science, math, engineering, and other related disciplines are all combined in the interdisciplinary area of artificial intelligence (AI). Natural language processing, image recognition, robotics, and decision-making algorithms are just a few examples of the many uses for AI.
The creation of algorithms for machine learning entails learning from data and producing predictions or judgements based on that data. This ability is essential for creating AI models that can spot patterns, anticipate outcomes, and gain knowledge from experience.
Machine learning needs proficiency in several programming languages, including Python, R, and MATLAB, and experience with machine learning frameworks such as TensorFlow and Keras. NLP is yet another necessary talent for creating AI systems that communicate with people using natural language.
Understanding human language, processing and analyzing text, and producing answers that are believable and natural are all components of NLP.
Programming skills in Python and Java are necessary for NLP, as is familiarity with NLP tools like NLTK and spaCy. Working with a lot of data in AI projects calls for data science abilities. These competencies include data extraction, data analysis, and data visualization. Data science needs knowledge of programming languages like Python, R, and SQL as well as hands-on experience with tools like Pandas and NumPy.
A broad range of abilities, including:
- Machine learning
- Natural Language Processing (NLP)
- Data science
- Deep learning
- Computing
- Robotics
- Problem-solving
are needed for the creation and application of AI systems. Programming expertise in a variety of languages, as well as familiarity with frameworks and development tools, are requirements for AI experts. These abilities can offer professionals a competitive edge and open doors to exciting career possibilities as AI technologies continue to advance.
1. Machine Learning Engineer
One of the most sought-after jobs in AI, machine learning engineers must possess strong software skills, be able to apply predictive models, and utilize natural language processing while working with massive data sets. Also, machine learning engineers are expected to know software development methodology, agile practices, and the complete range of modern software development tools right from IDEs like Eclipse and IntelliJ to the components of a continuous deployment pipeline. Start your journey as an AI/ML specialist with our AI & Machine Learning Bootcamp.
Average Salary: $121,106 (Glassdoor)
Preferred Qualifications: Hiring companies prefer candidates holding a master’s or doctoral degree in computer science or mathematics with working knowledge of modern programming languages like Python, Java, and Scala. These organizations usually prefer professionals with strong computer programming skills, expert mathematical skills, knowledge of cloud applications and computer languages, excellent communication, and analytical skills, and certifications like machine learning.
2. Robotic Scientist
Robots can automate jobs, but they require programmers working behind the scenes to ensure they function well. Robotic science is used for multiple functions from space exploration, healthcare, security, too many other scientific fields. Their primary function is to build mechanical devices or robots who can perform tasks with commands from humans. Other necessary skills required for this role include writing and manipulating computer programs, collaborating with other specialists, and developing prototypes.
Average Salary: $83,241 (Glassdoor)
Preferred Qualifications: A bachelor’s degree in robotic engineering/mechanical engineering/electro-mechanical engineering/electrical engineering is an essential prerequisite. Companies also look for professionals with specializations in advanced mathematics, physical sciences, life sciences, computer science, computer-aided design and drafting (CADD), physics, fluid dynamics and materials science, and related AI certification.
3. Data Scientist
Data scientists collect, analyze, and interpret large amounts of data by using machine learning and predictive analytics to gain insights beyond statistical analysis. They should have expertise in using Big Data platforms and tools, including Hadoop, Pig, Hive, Spark, and MapReduce. Data scientists are also fluent in programming languages, including structured query language (SQL), Python, Scala, and Perl, as well as statistical computing languages.
Average Salary: $117,345 (Glassdoor)
Preferred Qualifications: Data scientists are highly educated, with the majority holding master’s or doctoral degree, though an advanced degree in computer science is preferred, it is not a prerequisite. The most desired technical skills are in-depth knowledge of SAS and R, Python coding, Hadoop platform, experience working on cloud tools like Amazon’s S3, and the ability to understand unstructured data. Non-technical skills required include strong communication and analytical skills, intellectual curiosity, and business acumen.
4. Research Scientist
A research scientist is an expert in multiple artificial intelligence disciplines, including machine learning, computational statistics, and applied mathematics. In particular, these areas include deep learning, graphical models, reinforcement learning, computer perception, natural language processing, and data representation, graphical models, reinforcement learning, computer perception, natural language processing, and data representation.
Average Salary: $83,490 (Glassdoor)
Preferred Qualifications: A master’s or doctoral degree in computer science or a related technical field or equivalent practical experience is the basic requirement for this role. Companies also tend to prefer professionals who possess skills such as parallel computing, artificial intelligence, machine learning, knowledge of algorithms, and distributed computing, and benchmarking. Alongside these qualifications, an in-depth understanding of computer architecture and strong verbal and written communication skills are recommended for those interested in this field.
5. Business Intelligence Developer
Business intelligence developers are in high demand. Their primary job is to analyze complex data and look for current business and market trends, thereby increasing the profitability and efficiency of the organization. Not only are they masters of strong technical and analytical skills, but they also have sound communication and problem-solving skills. They are responsible for designing, modeling, building, and maintaining data for complex, extensive, and highly accessible cloud-based data platforms.
Average Salary: $90,430 (Glassdoor)
Preferred Qualifications: A bachelor’s degree in computer science, engineering, or a related field is required, or a combination of certifications and on-the-job experience are preferred for this role. Candidates with experience in data warehouse design, data mining, knowledge of BI technologies, SQL queries, SQL Server Reporting Services (SSRS), and SQL Server Integration Services (SSIS) and popular data science certifications are preferred.
The job opportunities available by the advent of artificial intelligence are only going to grow as the technology continues to innovate. Experts from Gartner predict, “AI will create more jobs than it eliminates.” Each role, however, requires education and training to fulfill the needs of the industry. Raj Mukherjee, Senior Vice President of Product at Indeed, puts it into perspective, “There are certain standard technical requirements, such as a computer science degree or programming skills. A background in programming languages like Python, Java, C/C++, and experience in artificial intelligence, machine learning, or natural language processing are some of the top skills employers look for in AI applicants.”
6. AI Product Manager
A person tasked with managing the creation, application, and management of AI-based goods and services is known as an AI product manager. To make sure that AI products and services satisfy corporate objectives and client demands, they collaborate with cross-functional teams that include software developers, data scientists, and business stakeholders.
Average Salary: $1,20,171 per year (Glass Door)
Required Qualifications: A background in computer science, data science, or engineering is common for AI product managers. Most employers prefer candidates with a master’s degree, though some may accept candidates with a bachelor’s degree in a related area. AI product managers should also be proficient in software development, project management, and AI technologies.
7. AI Consultant
An expert who advises companies and organizations on the creation and application of AI-based solutions is known as an AI consultant. An AI consultant’s job typically entails working with clients to comprehend their business requirements and creating tailored solutions that make use of AI technology to resolve challenging issues.
Average Salary: $1,00,512 per year (Glass Door)
Required Qualifications: A bachelor’s or master’s degree in a relevant subject, such as computer science, data science, or engineering, is usually required to work as an AI consultant. Strong knowledge of AI technologies and products is usually needed, as well as prior experience in software development, data analysis, or consulting. Excellent communication, leadership, and problem-solving abilities are required of AI consultants, as well as the capacity to collaborate with cross-functional teams and manage numerous tasks at once. An additional benefit is having certification in Intelligence technologies.
8. Robotics Engineer
An expert who creates, develops, and manages robots and robotic systems is a robotics engineer. An engineer who specializes in robotics will typically conduct market research and customer needs analysis, design and build robotic systems to meet those needs, test and troubleshoot systems, and constantly improve system performance.
Average Salary: $99,053 per year (Glass Door)
Required Qualifications: A bachelor’s or master’s degree in mechanical engineering, electrical engineering, or robotics is usually needed to become a robotics engineer. It is also usually necessary to have prior experience in robotics or a related field, like mechatronics. Robotics engineers need to be highly skilled in computing, control systems, mechanical design, and robotics design. Additionally, they should be able to work cooperatively with cross-functional teams and possess good problem-solving and communication skills. Some companies might favor applicants with robotics certifications.
9. NLP Engineer
An expert who creates and uses formulas and models to help computers comprehend, decipher, and produce human language is known as an NLP (Natural Language Processing) engineer. An NLP engineer’s duties usually include investigating and putting NLP techniques into practice, creating and refining NLP models, and integrating NLP systems into software programmes.
Average Salary: $1,17,534 per year (Glass Door)
Required Qualifications: A bachelor’s or master’s degree in computer science, data science, or a related field is usually required to become an NLP engineer. It is also usually necessary to have prior knowledge of NLP or a related field, like artificial intelligence, machine learning, or data mining. NLP programmers need to be highly technical, with knowledge of machine learning, statistical analysis, and NLP algorithms and models. Additionally, they should be able to work cooperatively with cross-functional teams and possess good problem-solving and communication skills. Candidates who have certifications in NLP or related areas may be preferred by some employers.
10. Research Assistant
When it comes to research in the area of artificial intelligence, a research assistant is typically in charge of gathering and analyzing data, testing new algorithms, and helping to create apps that use AI. Additionally, research assistants might be expected to write study summaries, academic papers, and presentations of their findings.
Average Salary: $40,990 per year (Glass Door)
Required Qualifications: A bachelor’s or master’s degree in computer science, artificial intelligence, or a closely related subject is usually required to work as a research assistant in this field. Along with previous expertise in data analysis, programming, and research methods, prior research experience in the fields of AI or machine learning is highly desired. Strong technical abilities are required, including mastery of data analysis, research methods, and programming languages like Python or R. Excellent verbal and written communication abilities as well as the capacity for cross-functional team collaboration are also imperative.
11.Deep Learning Engineer
A deep learning engineer is in charge of creating and putting into practise deep learning algorithms to address complicated issues in a variety of fields, including finance, healthcare, and autonomous vehicles. They are specialists in creating and building deep neural networks that can absorb a lot of information.
Average Salary: $1,37,474 per year (Glass Door)
Required Qualifications: Typically, a bachelor’s or master’s degree in computer science, data science, or a related area is required to become a deep learning engineer. Along with prior machine learning, programming, data analysis, and deep learning algorithm development and implementation experience, these skills are extremely desirable. Strong technical abilities are required, including competency in deep learning frameworks like TensorFlow or PyTorch, knowledge of programming languages like Python or C++, and expertise with cloud computing platforms. Additionally necessary are excellent problem-solving abilities and the capacity to collaborate with cross-functional teams.
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Conclusion
For those of you who are planning to pursue a spot in the AI field, you must start today by preparing yourself with the tools needed to execute the job successfully. Obtaining certifications in domains like machine learning and AI is a great place to start, and with the right education, the opportunities are endless.
You can also take up the AI and Machine Learning courses with Purdue University collaborated with IBM. This program gives you an in-depth knowledge of Python, Deep Learning with Tensor flow, Natural Language Processing, Speech Recognition, Computer Vision, and Reinforcement Learning.
