6 Artificial Intelligence (AI) Jobs to Consider in 2024 (2024)

Written by Coursera Staff • Updated on

Discover in-demand jobs and how to pursue a career in artificial intelligence.

6 Artificial Intelligence (AI) Jobs to Consider in 2024 (1)

The outlook is bright for artificial intelligence jobs, which is good news for anyone interested in the growing field of AI. India's artificial intelligence sector is forecasted to reach 17 USD billion by 2027, with anticipated growth rates ranging between 25 and 35 per cent annually from 2024 to 2027 [1]. Additionally, the demand for AI professionals in India is set to grow by 15 per cent per year until 2027 [1].

As the prevalence of AI has risen due to ChatGPT and other recent generative technology, you may be wondering what jobs are available in this field and how to land one. Continue reading to gain an overview of artificial intelligence careers and the skills and education you’ll need to pursue them.

6 artificial intelligence jobs to consider

The field encompasses several positions, ranging from AI engineers to data scientists. Learn more about specific jobs in AI and the average salaries you can expect to earn.

1. Artificial intelligence (AI) engineer

AI engineers use AI and machine learning techniques to develop applications and systems that help organisations become more efficient. They focus on developing the tools, systems, and processes that enable the application of AI to real-world problems. Data trains algorithms, helping them learn and perform better. AI engineers can help cut costs, increase productivity and profits, and make business recommendations.

Average base salary: ₹10,00,000 [2]

2. Machine learning engineer

Machine learning engineers research, build, and design the AI responsible for machine learning. They maintain and improve existing AI systems. A machine learning engineer often serves as a liaison with other data science team members, collaborating with the data scientists who develop models for building AI systems. They run experiments and tests, perform statistical analyses, and develop machine learning systems.

Average base salary: ₹10,00,000 [3]

3. Data engineer

Data engineers build systems that collect, manage, and convert raw data into usable information for data scientists, business analysts, and other data professionals to interpret. They make data accessible so that organisations can use it to evaluate and optimise their performance. Data engineering is a broad field with applications in nearly every industry.

Average base salary: ₹9.20,500 [4]

4. Robotics engineer

Robotics engineers develop robotic applications for many industries, including automotive, manufacturing, defence, and medicine. They design new products or assemble prototypes for testing. Some may work on-site at a manufacturing plant overseeing robots during production, whilst others monitor their performance in the real world. Robotics engineering combines elements of mechanical and electrical engineering with computer science.

Average base salary: ₹5,00,000 [5]

5. Software engineer

Software engineers, sometimes called developers, create software for computers and applications. They use programming languages, platforms, and architectures to develop anything from a computer game to network control systems. A software engineer may also test, improve, and maintain software built by other engineers. If you’re an analytical thinker who enjoys solving problems and enhancing digital systems, you may find this career rewarding.

Average base salary: ₹7,00,000 [6]

6. Data scientist

Data scientists determine what questions an organisation or team should ask and help them figure out how to answer those questions using data. They often develop predictive models to theorise and forecast patterns and outcomes. A data scientist might also use machine learning techniques to improve the quality of data or product offerings.

Average base salary: ₹12,00,000 [7]

Salary range and job outlook

The outlook is bright for AI jobs, which is good news for anyone working in the growing field of AI. To encourage leadership, excellence, and a unified AI ecosystem, the Indian government launched the National AI Portal of India, INDIAai, offering aspiring professionals, students, and others a central hub for the latest knowledge and opportunities.

Additionally, in 2021, the joint United States and Indian initiative, the US–India Artificial Intelligence (USIAI), was launched to increase opportunities for collaboration and eliminate barriers to India's AI growth. The growing drive to advance AI in India also offers opportunities for job growth in a high-paying industry. The annual wage for computer scientists averages ₹28,00,000 [8].

How to get a job in AI

When it comes to landing an AI job, you’ll want to consider the educational requirements and skills associated with a specific job role. These are the common ways to get a job in AI, but keep in mind that your path will vary depending on job type, level, and industry.

1. Research jobs in AI.

The first step to getting started is to research which jobs within the field of AI you’d like to pursue so that you can tailor your education and build your skills. In addition to the six jobs listed above, you may come across the following roles in researching a career in AI:

  • Director of analytics: Directs the data analytics and data warehousing departments and is in charge of research, development, and implementation of relevant data systems

  • Principal scientist: Designs, executes, and documents research experiments in many fields and industries as part of a research team

  • Computer vision engineer: Uses computer vision and machine learning research to solve real-world problems in real-time

  • Algorithm engineer: ​​Assists clients in understanding more prominent data trends and reporting on these trends

  • Computer scientist: Designs innovative uses for new and existing computing technology, solving computing problems in various industries

  • Statistician: Creates or uses different mathematical or statistical theories and methods to gather and explain the numerical data findings for a given project

  • Research engineer: Utilises educated research findings to create a reliable answer for problems at hand

2. Consider earning a degree.

Many jobs in AI require a bachelor’s degree. Often, AI professionals obtain undergraduate degrees in computer science, mathematics, or a related field. However, whilst not mandatory, obtaining a master's degree can enhance your skill set, potentially increasing your earning potential.

3. Build AI skills.

You can expect to hone several skills when preparing to work in AI. While you can explore many branches of AI, you’ll find that most have some core commonalities. You can build many of these skills through self-guided practice, learn via online courses or boot camps, or develop through coursework when earning a degree.

Technical skills

You’ll notice many jobs in AI rely on proficiency in programming languages and coding. Coding is typically one of the first skills learned by many people interested in this field. Expect to also work with a variety of computer systems. A few essential technical skills to build include:

  • General-purpose languages: Python and C/C++

  • Database management: Apache Cassandra, Couchbase, DynamoDB

  • Data analysis and statistics: MATLAB, R, Pandas

  • AI platforms: Microsoft Azure AI, Google Cloud AI, IBM Watson

  • Data acquisition systems: Physical sensors and wireless sensors

  • Digital marketing goals and strategies

  • Industry knowledge

Workplace skills

Workplace skills aren’t always something you can learn through courses but rather through experience. Consider working on these skills when thinking about pursuing a career in AI:

  • Communication

  • Collaboration

  • Analytical thinking

  • Problem-solving

  • Management and leadership

4. Earn a certification.

If you already have your undergraduate degree in a field related to AI, consider enroling in courses to learn the technical skills. Even if you don’t have a degree, certifications demonstrate to potential employers that you’re serious about your career goals and investing in your skills. Some AI certifications and certificate programmes to consider include:

  • ARTIBA: Artificial Intelligence Engineer

  • IBM Applied AI Professional Certificate

  • IBM AI Engineering Professional Certificate

  • Google Advanced Data Analytics Professional Certificate

5. Apply to entry-level jobs.

Once you feel confident with your level of training, start doing research and applying for jobs. Many entry-level AI jobs, such as software engineer or developer, will indicate “entry-level” or “junior” in the job description. Those that require less than three years of experience are typically fair game.

If you need help in your job search, try applying for internships or starting a freelance project or a hackathon to sharpen your skills. You’ll receive feedback on your work and develop relationships that may benefit you in the future.

Start preparing for a career in AI today with Coursera

AI is a developing field that is changing the way we use technology. To get ahead of the crowd and learn about AI, consider programmes like the IBM Applied AI or AI Engineering Professional Certificates to become job-ready within months. You can learn Python, build a chatbot, and explore machine learning with an industry leader in technology.

Or, if you plan to earn a degree online, you'll find a couple of options available through Coursera. You could pursue a Bachelor of Science in Computer Science from the University of London or even a Master of Science in Data Science from the University of Colorado Boulder.

Updated on

Written by:

C

Coursera Staff

Editorial Team

Coursera’s editorial team is comprised of highly experienced professional editors, writers, and fact...

This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

6 Artificial Intelligence (AI) Jobs to Consider in 2024 (2024)
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