13 Exciting Artificial Intelligence Careers in 2024

Artificial intelligence (AI) is no longer a futuristic concept—it’s a present-day reality already transforming industries and career opportunities. From self-driving cars to smart assistants, AI is changing how we live, work, and interact—and it’s driving demand for skilled professionals who can navigate this evolving field.

However, we can’t take AI careers for granted. It takes a special breed of experts who can develop, implement, and manage AI systems. And demand is skyrocketing. This rapid growth is opening doors to a variety of exciting and lucrative careers in AI.

Below, we’ll explore 13 AI careers in high demand in 2024 and beyond. Whether you’re a founder, entrepreneur, developer, or just someone considering a career shift, understanding these potential roles can help you understand and prepare for the future of work.

13 AI careers in 2024

As AI continues to transform industries, numerous career paths have emerged in this field. This section explores AI-focused roles, including machine learning engineer, data scientist, and AI ethics officer. These positions are not only at the cutting edge of technology but also play critical roles in shaping how AI is developed, implemented, and governed across various sectors. Let’s dive in.

1. Machine learning engineer

Machine learning engineers are the architects of intelligent systems. They design, build, and deploy algorithms that allow machines to learn from data and make predictions. This AI job involves creating models that can process vast amounts of information, recognize patterns, and improve over time without human intervention.

Machine learning engineers work closely with data scientists to refine models for accuracy and efficiency in real-world applications.

Why it’s in-demand in 2024:

The demand for machine learning engineers is skyrocketing as industries increasingly rely on automated decision-making and predictive analytics. From healthcare to finance, businesses want to harness the power of AI to gain insights, improve operations, and innovate.

The employment of computer and information research scientists (including machine learning engineers) is projected to grow 15% from 2019 to 2029, much faster than the average for all occupations.

Skills needed:

• Proficiency in programming languages (Python, R)

• Familiarity with machine learning frameworks (TensorFlow, PyTorch)

• Data modeling and statistical analysis

• Strong problem-solving skills and the ability to work with large datasets

Career path:

• Degree in computer science, artificial intelligence, or a related field

• Advanced degrees (master’s or PhD) can be advantageous

• Certifications in machine learning and data science

• Hands-on experience in projects and internships

• Continuous learning to keep up with AI advancements

2. Data scientist

Data scientists extract insights from complex datasets to drive decision-making and strategy. They collect, analyze, and interpret large volumes of data to identify trends, patterns, and correlations.

Data scientists use statistical techniques and machine learning algorithms to develop predictive models, optimize processes, and provide actionable insights to stakeholders.

Why it’s in-demand in 2024:

Data scientists are in high demand as organizations increasingly rely on data-driven decision-making. Turning raw data into actionable insights is critical for competitive advantage.

The demand for data scientists is expected to grow by 28% by 2026. With businesses across various sectors seeking to leverage data for innovation and efficiency, data scientists will continue to be essential in 2024 and beyond.

Skills needed:

• Expertise in statistical analysis, data mining, and machine learning

• Proficiency in programming languages (Python, R, SQL)

• Data visualization skills (Tableau, Power BI)

• Strong analytical and problem-solving abilities

Career path:

• Degree in data science, computer science, mathematics, or a related field

• Advanced degrees (master’s or PhD) for deeper knowledge

• Certifications in data analytics and machine learning

• Practical experience through internships, projects, and research

3. AI product manager

AI product managers bridge the gap between technology and business by overseeing the development and implementation of AI products. They define product vision, strategy, and product roadmap prioritization to maintain alignment with business goals.

AI product managers collaborate with cross-functional teams (including cloud engineers, data scientists, and marketers) to bring AI products to market and guarantee their success.

Why it’s in-demand in 2024:

Businesses need professionals who can translate AI capabilities into marketable products and services. AI is expected to contribute $15.7 trillion to the global economy by 2030. AI product managers will help drive this growth by bringing innovative AI solutions to market.

Skills needed:

• Understanding AI technologies, machine learning, and data science

• Product management, project management, and strategic planning

• Effective communication and leadership abilities

• Ability to manage cross-functional teams and stakeholders

Career path:

• Background in product management, business administration, or a related field

• Knowledge of AI and machine learning, often through degrees or certifications

• Experience in managing technology products and leading cross-functional teams

4. AI research scientist

AI research scientists are at the forefront of advancing AI technologies through research and experimentation. They work on developing new algorithms, models, and methodologies to solve complex problems.

AI research scientists typically publish their findings in academic journals, contribute to the scientific community, and collaborate with industry partners to apply their research in practical applications.

Why it’s in-demand in 2024:

AI research scientists drive innovation and push the boundaries of what AI can achieve. Their work contributes to the development of cutting-edge technologies and applications. AI and machine learning AI jobs are among the top emerging roles in the job market.

Skills needed:

• Expertise in machine learning, neural networks, and deep learning

• Strong programming skills (Python) and proficiency in AI frameworks (TensorFlow, PyTorch)

• Research skills, critical thinking, and ability to publish scientific papers

• Collaboration and communication skills

Career path:

• Advanced degrees (master’s or PhD) in AI, computer science, or related fields

• Academic research experience and publications in reputable journals

• Networking within the AI research community and collaborating on projects

5. AI data engineer

Data engineers are responsible for building and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. They design and implement data pipelines to make data accessible for analysis and machine learning.

Data engineers work closely with data scientists and analysts to maintain data quality and availability.

Why it’s in-demand in 2024:

Data engineers are essential for creating robust data pipelines that support AI and machine learning projects. Data engineering roles are among the fastest-growing jobs in the tech industry.

In 2024, data engineers will continue to be in high demand to support the expanding needs of data-centric businesses.

Skills needed:

• Proficiency in big data technologies (Hadoop, Spark)

• Strong programming skills (Python, Java, SQL)

• Knowledge of data warehousing, ETL (extract, transform, load) processes, and cloud platforms (AWS, Google Cloud)

• Problem-solving abilities and attention to detail

Career path:

• Degree in computer science, data engineering, or a related field

• Certifications in big data technologies and cloud platforms

• Practical experience through internships and projects

6. Computer vision engineer

Computer vision engineers develop algorithms that allow machines to interpret and understand visual data from the world. They work on applications such as image recognition, object detection, and video analysis.

Computer vision engineers leverage machine learning and deep learning techniques to create models that can process and analyze visual information.

Why it’s in-demand in 2024:

Computer vision is transforming industries such as healthcare, automotive, and security. The ability to develop systems that can interpret visual data is in high demand. The global data visualization and computer vision market size is expected to reach $19.1 billion by 2027 (growing at a CAGR of 7.6%).

In 2024, computer vision engineers will be sought after to develop innovative applications that rely on visual data.

Skills needed:

• Expertise in image processing, computer vision algorithms, and deep learning

• Proficiency in programming languages (Python) and libraries (OpenCV, TensorFlow)

• Knowledge of software development and frameworks for building and deploying computer vision models

• Strong problem-solving skills and creativity

Career path:

• Degree in computer science, electrical engineering, or a related field

• Advanced degrees for deeper knowledge

• Certifications in computer vision and hands-on experience with projects and internships

7. Natural Language Processing (NLP) engineer

NLP engineers develop systems that enable machines to understand, interpret, and generate human language. They work on chatbots, language translation, and sentiment analysis applications. NLP engineers use machine learning and deep learning techniques to create models that can process and analyze textual data.

Why it’s in-demand in 2024:

With the increasing demand for human-computer interaction and the need to process large volumes of textual data, NLP engineers are in high demand. Industries such as customer service, healthcare, and finance leverage NLP to improve user experiences and automate processes. The global NLP market is expected to grow from $11.6 billion in 2020 to $35.1 billion by 2026.

Skills needed:

• Expertise in natural language processing, linguistics, and deep learning

• Proficiency in programming languages (Python) and libraries (NLTK, spaCy)

• Knowledge of machine learning and statistical analysis

• Strong problem-solving skills and creativity

Career path:

• Degree in computer science, linguistics, or a related field

• Advanced degrees for deeper knowledge

• Certifications in natural language processing and hands-on experience with projects and internships

8. Robotics engineer

Robotics engineers design, build, and maintain robots and robotic systems. They work on applications ranging from manufacturing and healthcare to exploration and entertainment.

Robotics engineers leverage AI, machine learning, and mechanical engineering principles to create systems that can perform tasks autonomously or assist humans in various activities.

Why it’s in-demand in 2024:

From autonomous vehicles to robotic surgery, robotics applications are extensive and growing. The robotics market is expected to grow from $76.6 billion in 2020 to $176.8 billion by 2025.

Skills needed:

• Proficiency in robotics software and hardware

• Knowledge of AI and machine learning algorithms

• Expertise in mechanical engineering and electrical systems

Career path:

• Degree in robotics, mechanical engineering, or a related field

• Advanced degrees for specialized knowledge

• Certifications in robotics and hands-on experience with projects and internships

9. AI hardware engineer

AI hardware engineers design and develop specialized hardware to support AI and machine learning applications. They focus on creating chips, processors, and other components that optimize the performance and efficiency of AI algorithms.

AI hardware engineers work on advancing technologies to improve computational power and reduce energy consumption for AI tasks.

Why it’s in-demand in 2024:

The increasing complexity of AI models and the demand for faster processing speeds are driving the need for specialized hardware. By 2025, AI-related semiconductors might account for almost 20% of all hardware demand.

Skills needed:

• Expertise in hardware design and development

• Proficiency in programming languages (C++, Verilog)

• Knowledge of AI algorithms and machine learning frameworks

• Experience with FPGA and ASIC design

• Ability to optimize hardware performance

Career path:

• Degree in electrical engineering, computer engineering, or a related field

• Advanced degrees for specialized knowledge in hardware design

10. AI ethics officer

AI ethics officers guarantee that AI technologies are developed and used responsibly. They identify and mitigate ethical issues related to AI, such as bias, AI privacy, and transparency.

AI ethics consultants collaborate with developers, business leaders, and policymakers to create guidelines and frameworks that promote ethical AI practices.

Why it’s in-demand in 2024:

As AI becomes more integrated into society, ethical concerns are increasingly important. Businesses and governments are under pressure to build AI systems that are fair, transparent, and accountable.

49% of executives have guidelines or policies for the ethical use of AI, and another 37% plan to roll out policies soon.

Skills needed:

• Knowledge of AI and machine learning principles

• Understanding of ethical frameworks and regulations

• Strong analytical and problem-solving skills

• Excellent communication and collaboration abilities

Career path:

• Degree in computer science, philosophy, ethics, or a related field

• Advanced degrees in AI ethics or law for specialized knowledge

11. AI infrastructure engineer

AI infrastructure engineers create and manage the systems and tools that support AI development and deployment. They design and maintain the infrastructure needed for training, testing, and deploying machine learning models, guaranteeing they are scalable, reliable, and efficient.

AI infrastructure engineers work closely with data scientists and machine learning engineers to optimize computational resources and streamline AI workflows.

Why it’s in-demand in 2024:

AI infrastructure engineers are essential for enabling efficient AI development and deployment. By the end of 2024, 75% of enterprises will shift from piloting to operationalizing AI, driving a fivefold increase in streaming data and analytics infrastructures.

Skills needed:

• Proficiency in cloud platforms (AWS, Azure, Google Cloud)

• Strong programming skills (Python, Java, Scala)

• Knowledge of containerization and orchestration tools (Docker, Kubernetes)

• Experience with big data technologies (Hadoop, Spark)

• Problem-solving skills and ability to optimize computational resources

Career path:

• Degree in computer science, AI technology, or a related field

• Certifications in cloud computing and big data technologies

12. Audio intelligence engineer

Audio intelligence specialists develop and optimize systems that process, analyze, and understand audio data. This role includes working on speech recognition, audio event detection, and sound classification technologies.

Audio intelligence specialists use machine learning and signal processing techniques to create applications that interpret and respond to audio inputs.

Why it’s in-demand in 2024:

Healthcare, security, and entertainment industries leverage audio intelligence to improve user experiences and develop innovative solutions. With the rise of smart speakers, voice-activated assistants, and advanced audio analytics, the demand for audio intelligence specialists is growing.

The global speech and voice recognition market size is expected to reach $31.82 billion by 2025.

Skills needed:

• Expertise in audio signal processing and machine learning

• Proficiency in programming languages (Python, MATLAB) and frameworks (TensorFlow, Keras)

• Knowledge of speech recognition and natural language processing

• Strong analytical and technical skills

Career path:

• Degree in computer science, electrical engineering, or a related field

• Advanced degrees for specialized knowledge

• Certifications in audio processing and machine learning

• Hands-on experience with projects and internships

13. AI model trainer

AI model trainers train machine learning models by selecting and preparing training data, configuring model parameters, and optimizing performance. They work closely with data scientists and machine learning engineers to guide models effectively and meet desired accuracy and performance metrics.

AI model trainers also monitor training processes and fine-tune models to improve results.

Why it’s in-demand in 2024:

As AI applications become more prevalent, the demand for high-quality models that perform accurately across various scenarios is increasing. With businesses and industries increasingly relying on AI for automation, prediction, and decision-making, AI professionals will become essential.

Skills needed:

• Expertise in machine learning algorithms and model training techniques

• Proficiency in programming languages (Python, R)

• Experience with machine learning frameworks (TensorFlow, PyTorch)

• Ability to work with large datasets and optimize model performance

Career path:

• Degree in computer science, data science, or a related field

• Certifications in machine learning and AI

• Hands-on experience with training and optimizing machine learning models

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