Jobs in AI and the Right Artificial Intelligence Skills You Need to Stand Out

Artificial Intelligence is shaping the future, and its impact on various industries will continue to grow. As you explore career opportunities in this exciting field, acquire the necessary skills. Staying updated with the latest advancements will be essential for success. Embrace the potential of AI and embark on a journey that leads to a fulfilling and rewarding career in the world of intelligent machines.

The term artificial intelligence

Artificial Intelligence (AI) technology has been rapidly gaining popularity in recent years, making its way into various aspects of our daily lives. From robots serving food in restaurants to self-driving cars, the applications of AI are becoming increasingly prevalent. The term “artificial intelligence” was coined by John McCarthy, an American computer scientist, and it refers to the science and engineering of creating intelligent machines and computer programs. AI aims to develop software and systems that mimic human thinking, learning, decision-making, and problem-solving capabilities, enabling machines to perform tasks in a human-like manner through learning from experience.

Despite concerns about AI potentially replacing human jobs, a Gartner study predicts that AI will create 2.8 million jobs by 2020. AI is a broad field, encompassing various branches such as general artificial intelligence, machine learning, expert systems, data mining, and more. The demand for AI capabilities spans across industries, including gaming, robotics, face recognition software, weaponry, speech recognition, vision recognition, expert systems, and search engines. For individuals considering a career in this rapidly evolving field, here are the top five jobs in artificial intelligence and the skills required to excel in these roles.

As the world embraces AI and data analytics, individuals like Nayan Panday have recognized the potential for growth in this domain. Nayan’s interest in research and analytics led him to learn Python and AI/ML, setting him on a path to success in the AI field. To learn more about Nayan’s journey with Simplilearn’s AI and ML Certification, read his comprehensive review.

Top Artificial Intelligence Skills for Jobs in AI

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 of AI.

The creation of algorithms for machine learning entails learning from data and producing predictions or judgments 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:

1. Machine learning
2. Natural Language Processing (NLP)
3. Data Science
4. Deep learning
5. Computing
6. Robotics
7. 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.

Top Most Promising Careers in AI

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.

Average Salary: $121,106

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 that 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

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

Preferred Qualifications: Data scientists are highly educated, with the majority holding master’s or doctoral degrees, 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, the 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

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, 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

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), 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, and 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

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

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

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 programs.

Average Salary: $1,17,534 per year

8. 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

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 practice 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

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.

FAQ

What are the most in-demand AI jobs?

• Data scientist: Data scientists are responsible for collecting, cleaning, and analyzing data to extract insights. They need to have strong skills in mathematics, statistics, and programming.
• Machine learning engineer: Machine learning engineers are responsible for developing and deploying machine learning models. They need to have strong skills in machine learning algorithms and programming.
• Natural language processing engineer: Natural language processing engineers are responsible for developing and deploying natural language processing models. They need to have strong skills in natural language processing algorithms and programming.
• Computer vision engineer: Computer vision engineers are responsible for developing and deploying computer vision models. They need to have strong skills in computer vision algorithms and programming.
• Robotics engineer: Robotics engineers are responsible for designing, building, and programming robots. They need to have strong skills in mechanical engineering, electrical engineering, and programming.
• AI researcher: AI researchers are responsible for conducting research in artificial intelligence. They need to have strong skills in mathematics, statistics, computer science, and programming.

What are the right artificial intelligence skills you need to stand out?

• Strong programming skills: You need to be proficient in programming languages such as Python, R, and Java.
• Knowledge of machine learning algorithms: You need to have a good understanding of machine learning algorithms such as supervised learning, unsupervised learning, and reinforcement learning.
• Experience with data science tools: You need to be familiar with data science tools such as Hadoop, Spark, and Tableau.
• Creativity and problem-solving skills: You need to be able to think creatively and solve problems.
• Communication skills: You need to be able to communicate your ideas effectively to both technical and non-technical audiences.

How can I get started in a career in AI?

• Get a degree in computer science or a related field: This will give you the foundation in mathematics, statistics, and programming that you need to succeed in AI.
• Take online courses in AI: There are many online courses available that can teach you the basics of AI.
• Work on personal projects: This is a great way to gain experience and build your portfolio.
• Network with people in the AI industry: Attend conferences, meet-ups, and workshops to meet people who work in AI.
• Contribute to open source projects: This is a great way to get involved in the AI community and learn from others.

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 is a great place to start, and with the right education, the opportunities are endless.