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A career in artificial intelligence offers enormous growth potential due to the rapid growth of the AI sector. Many organizations are striving to quickly hire qualified — or even semi-qualified — AI experts, so AI salaries are trending upward.
To be sure, AI is highly complex, and its complexity requires professional expertise to build a successful career. Still, for tech professionals, AI offers an incredible open door to get in on the ground floor of many emerging career paths.
In this guide, we look at 10 AI career paths to consider, as well as core issues for you to be aware of as you consider this career shift.
TABLE OF CONTENTS
AI Careers: Leading Positions
The artificial intelligence career positions below range from AI consultant to AI programmer to research scientist, but many of these positions may overlap with one another. Indeed, the actual duties of AI careers are shifting as the AI sector itself undergoes rapid growth.
1. AI Consultant
The AI consultant is currently one of the most sought-after professionals in the artificial intelligence sector. AI consultants are responsible for advising and supporting businesses and other organizations in implementing AI. Responsibilities include everything from managing implementation projects to ensuring AI software are compatible with an organization’s needs.
Because of these varying duties, AI consultants must understand AI in its entirety. They must understand complex topics such as machine learning and deep learning, as well as how to construct and use algorithms.
Certification or Degree
- Certified Artificial Intelligence Consultant (CAIC™) offered by USAII.
- Certified Artificial Intelligence Practitioner (CAIP) offered by CertNexus.
Skills
- Computing expertise — proficiency in programming languages like Java, C++, Python, and Ruby.
- Technical abilities.
- Mathematical mastery.
- Knowledge of data processing and visualization techniques.
Salary Range
Data from Glassdoor shows that the average salary for an AI consultant is $172,835 per year.
Career Advancement Opportunities
AI consultants often advance to managerial positions, overseeing teams of consultants and driving AI strategy for organizations.
To learn about AI certifications that can advance your career, see our guide, 30 Top AI Certifications.
2. AI Prompt Specialist
Also known as prompt engineers, these specialists are tasked with developing prompts to be used with generative AI tools. Some of these tools include ChatGPT and Midjourney.
Prompts guide these AI tools and help them produce specific results. Prompt specialists must understand how these tools work and how best to communicate with them. Because of the wide use of these tools, prompt specialists can work in a wide range of industries, from advertising to manufacturing.
Certification or Degree
- Prompt Engineering for ChatGPT by Vanderbilt University.
- ChatGPT Prompt Engineering for Developers by OpenAI and DeepLearning.AI.
- The Complete Prompt Engineering for AI Bootcamp.
- ChatGPT Masterclass: The Guide to AI & Prompt Engineering – Udemy.
Skills
- Expertise in natural language processing and understanding to generate effective prompts for AI systems.
- Proficiency in developing algorithms and models to create relevant and engaging prompts for various applications.
- Linguistic proficiency.
- NLP knowledge.
- Creative and adaptable writing.
- Iterative testing and learning.
Salary Range
The salary range for an AI prompt specialist can vary based on factors such as location, level of experience, and company size. On average, the salary for an AI prompt specialist ranges from $80,000 to $150,000 per year. However, in high-demand markets or with additional specialized skills, the salary range can exceed $150,000.
Career Advancement Opportunities
As an AI consultant gains experience and demonstrate proficiency in creating effective prompts for AI systems, they may advance to a senior AI prompt specialist role. In this position, they may lead prompt generation projects, mentor junior team members, and have higher-level responsibilities.
3. AI Programmer
A career as an AI programmer requires expertise in using algorithms to program AI-based services, apps, and software. These programmers are also responsible for training machines to produce human-like input and for troubleshooting issues within AI-based tools.
AI programmers must have a solid handle on programming languages such as Python and Java. They must also understand the basics of software development and have an extensive knowledge of how AI concepts support software development.
Certification or Degree
Skills
- Programming languages: Proficiency in languages such as Python, Java, C++, or R is essential for AI programming.
- Knowledge of machine learning algorithms, techniques, and frameworks such as TensorFlow, Keras, or Scikit-learn.
- Algorithm design and optimization.
- Problem-solving.
Salary Range
Our research found that AI programmers can expect to earn an average salary of around $143,000 per year in the United States. Salaries can be higher for those with advanced degrees, specialized skills, and several years of experience in the field.
Career Advancement Opportunities
AI programmers could transition into a research-focused role, which involves conducting research in an array of advanced artificial intelligence topics, publishing papers, and contributing to advancements in the field.
For more information about generative AI providers – all of which hire AI experts – read our in-depth guide: Generative AI Companies: Top 20 Leaders
4. AI Developer
While similar to programmers, AI developers develop and design the AI-based services, apps, and software organizations use. For example, AI developers ensure that the user interface of an AI-based tool is easy to use.
AI developers also test software applications to ensure they result in the desired outcomes. In some cases, AI programmers and developers will work alongside one another.
Developers must have solid problem-solving skills and creativity while also understanding data engineering and analytics. This AI career tends to be highly lucrative.
Certification or Degree
- IBM AI Developer Professional Certificate on Coursera.
- Global Tech Council’s Certified Artificial Intelligence (AI) Developer certification.
- Certified AI Developer by Blockchain Council.
Skills
- Proficiency in programming languages such as Python, Java, or C++.
- Knowledge of machine learning algorithms and techniques.
- Experience working with big data technologies like Hadoop, Spark, or Apache Flink.
- Strong problem-solving skills and analytical thinking.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Familiarity with software development best practices and version control systems like Git.
Salary Range
Data from ZipRecruiter shows that the average salary for an AI developer in the US in 2024 is $129,348 per year, or $62 per hour.
Career Advancement Opportunities
AI developers can transition into a senior AI developer, an AI architect, a research role, or become an AI consultant.
5. Data Scientist
A data scientist’s key responsibility is solving complex problems using data. Data scientists perform a wide range of duties, including building models using programming languages, finding patterns in data sets, communicating insights to stakeholders, and consulting with organizations on how to best use their data.
Data science plays a crucial role in AI. Scientists work to build the advanced algorithms necessary to uncover complex patterns. Those patterns can then be used to train still more advanced AI models.
Certification or Degree
- IBM Data Science Professional Certificate on Coursera.
- The Data Science Council of America’s (DASCA) Senior Data Scientist (SDS) certification program.
- Azure Data Scientist Associate certification from Microsoft.
Skills
- Strong knowledge of programming languages such as Python, R, or SQL.
- Proficiency in data analysis and statistical tools.
- Familiarity with machine learning algorithms and techniques.
- Ability to work with large datasets and databases.
- Attention to detail and accuracy in data analysis.
Salary Range
According to Indeed, the average salary for a data scientist is $124,337 per year in the United States.
Career Advancement Opportunities
At a more senior level, data scientists may have the opportunity to become a chief data officer, where they are responsible for the organization’s data strategy, governance, and ensuring that data-driven insights are used to drive business decisions.
6. AI Research Scientist
As AI continues to evolve, organizations will need to find innovative ways to use it. A career as an AI research scientist involves exploring the use of AI to uncover new opportunities – most of which can now hardly be imagined. They also build algorithms and perform experiments to test new AI methods.
Research scientists must be highly inquisitive and creative. They must also have a firm grasp on complex subjects such as statistics, data analytics, machine learning, and natural language processing.
Certification or Degree
- Certified Research Scientist (CRS) offered by the American Statistical Association (ASA).
- Certified AI Research Scientist (CAIRS) program offered by American Institute of Business and Management.
Skills
- Strong background in computer science, mathematics, and statistics.
- Deep understanding of machine learning algorithms and neural networks.
- Proficiency in programming languages such as Python, Java, or C++.
- Ability to analyze data and draw meaningful insights from it.
- Experience with AI research projects and publications.
- Continuous learning and staying updated on the latest developments in the field of AI.
Salary Range
According to Glassdoor, the estimated pay for an AI research scientist is $171,630 per year.
Career Advancement Opportunities
As AI technology evolves, there is a growing need for professionals who can address the ethical considerations and policy implications of AI. AI research scientists could transition into roles focused on AI ethics, responsible AI development, and policy-making related to AI technologies. Alternatively, they could transition into a career in academia, teaching AI courses and conducting research at universities or research institutions.
7. Machine Learning Engineer
The machine learning engineer plays a critical role in the development of AI programs, applications, and software. Machine learning engineers work to design the models and algorithms that make AI work.
The process of designing these models requires the ML engineer to organize data, test models, program AI models using languages like Python, and perform production-level tasks to support ML development.
Certification or Degree
- Professional Machine Learning Engineer by Google.
- Andrew Ng’s Machine Learning Specialization on Coursera.
- IBM Machine Learning Professional Certificate on Coursera.
- AWS Certified Machine Learning – Specialty on Coursera.
Skills
- Strong knowledge of machine learning algorithms and techniques.
- Proficiency in programming languages such as Python, R, or Java.
- Familiarity with data manipulation and analysis tools like NumPy, Pandas, and Scikit-learn.
- Experience with data visualization libraries like Matplotlib and Seaborn.
- Understanding of statistics and probability theory.
- Knowledge of deep learning frameworks such as TensorFlow or PyTorch.
- Ability to work with big data technologies like Hadoop, Spark, or SQL.
- Strong problem-solving and analytical skills.
- Good communication and teamwork abilities.
Salary Range
Data from Indeed shows that the average salary for a machine learning engineer is $165,685 per year.
Career Advancement Opportunities
ML engineers can become a machine learning researchers with a focus on developing new algorithms, techniques, and technologies within the field of ML. This role requires a strong background in computer science and mathematics.
To learn about ML certifications that can advance your career, see our guide, 6 Best Machine Learning Certifications
8. Deep Learning Engineer
While deep learning is a branch of machine learning, deep learning goes beyond machine learning in that it enables AI models to learn and make their own decisions. In other words, deep learning enables machines to learn and act in manner similar to the human brain.
Deep learning engineers use this process to build highly intelligent AI models, most often for the purpose of predictive analytics. These engineers must be experts in machine learning, neural networking, data science, and programming.
Certification or Degree
- IABAC’s Certified Deep Learning Expert Certification (CDLE – AI3060).
- Certified Deep Learning Associate by Skillfloor.
- Certified Deep Learning Expert Course offered by Datamites Global Training Institute.
Skills
- Proficiency in programming languages such as Python, C++, or Java.
- Strong foundation in mathematics, especially linear algebra, calculus, and statistics.
- Understanding of machine learning algorithms and techniques.
- Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Experience with data preprocessing, feature engineering, and model evaluation.
- Knowledge of neural network architectures and how to design and optimize them.
Salary Range
The average salary for a deep learning software engineer is $148,300 per year, per Glassdoor.
Career Advancement Opportunities
With experience and proven expertise in deep learning, professionals can advance into leadership positions such as technical lead, team manager, or project manager, where they can oversee and guide teams of AI/ML engineers.
9. Natural Language Processing (NLP) Engineer
Natural language processing, or NLP, refers to a computer’s ability to understand human language. NLP is a major force behind popular AI tools such as chatbots like ChatGPT.
A career as an NLP engineer requires deep expertise in programming AI models and systems that can understand human language. This means that while NLP engineers must understand programming and AI, they must also be experts in language and linguistics.
Certification or Degree
- Natural Language Processing Specialization on Coursera (offered by DeepLearning.AI).
- Natural Language Processing (NLP) with Python for Machine Learning on Udemy.
- Natural Language Processing in TensorFlow on Coursera (offered by Deeplearning.AI).
- Natural Language Processing Nanodegree by Udacity.
Skills
- Proficiency in programming languages such as Python, Java, or C++.
- Strong knowledge of natural language processing techniques and algorithms.
- Familiarity with data preprocessing and text processing tools.
Salary Range
According to Talent.com, the average NLP engineer salary is $170,000 per year. Entry level positions start at $130,000 per year, while many experienced workers make up to $208,400 per year.
Career Advancement Opportunities
An NLP engineer might transition into a role as an NLP researcher. These researchers focus on advancing the field through theoretical and applied research, publishing papers, and collaborating with academic institutions. Optionally, they can become an NLP architect and be responsible for designing and implementing the overall architecture of NLP systems within an organization.
10. Robotics Engineer
Robotics engineers are tasked with using machines and algorithms to build robots, typically software robots but sometimes “humanoid” and/or mechanical robots. They’re also responsible for testing and maintaining robotic systems and machines across a wide range of industries, from manufacturing to retail.
The skills required to be a robotics engineer are a unique – and complex – mix. Not only do you need to understand AI, programming, and mathematics, but in some cases you must also have mechanical skills.
Certification or Degree
- Robotics Engineering & Applications offered by L&T EduTech on Coursera.
- Certified Robotic Engineer Courses by SMEC.
- Certified Robotics Engineer (CRE) certification program offered by the Institute of Electrical and Electronics Engineers (IEEE).
Skills
- Strong understanding of robotics principles and systems.
- Proficiency in programming languages such as C++, Python, and MATLAB.
- Knowledge of electronics and electrical systems.
- Ability to design, build, and troubleshoot robotics systems.
- Strong analytical and mathematical skills.
- Understanding of mechanical engineering principles.
- Familiarity with robotic sensors and actuators.
Salary Range
On average, robotics engineers can expect to earn between $110,638 and $139,428 per year, per salary.com.
Career Advancement Opportunities
Robotics engineers can advance their careers by specializing in specific areas of robotics, such as autonomous navigation, computer vision, or industrial automation.
How to Start a Career in Artificial Intelligence
If a career in AI seems like a fit for you, there are a few steps you must take to get started, including selecting a career path, obtaining the proper training, and building a portfolio to showcase your experience to potential employers.
Select an AI Career Path
The first step is to choose an AI career path. This choice should be based on factors such as your future career goals, current skill set, and interests.
For example, while all aspects of AI require the use of math, some careers will be more math-heavy than others. If you’re a numbers person, a career as a data scientist or programmer might be a solid choice for you.
However, if you simply enjoy being on the bleeding edge of technology, you may opt for robotics. As AI is a wide-open field, be sure to do your research to uncover the constantly shifting AI job market.
Obtain an AI-Focused Certification or Degree
The next step is to obtain the proper education and training for your selected career path. Education will vary, depending on what you choose.
For example, if you wish to start a career as an AI programmer, you’ll need to understand programming languages such as Python, as well as AI-specific concepts like machine learning. On the other hand, an AI consultant will need to understand data science and the many layers of AI.
There are various methods for obtaining the required training. For example, you can take various AI-related courses online or opt for a traditional college program. Often, organizations will also offer internship programs where students can learn AI in a real-world environment.
Build your AI portfolio
Building your portfolio will ensure you have proof of your AI-specific skill set. To build a portfolio, complete AI projects that pertain to your chosen career path. For example, build a machine learning model or algorithm or design a chatbot.
Apply to Entry-Level Jobs
Once you have obtained the necessary education and built a portfolio, it’s time to start applying for entry-level AI jobs. Look for opportunities at AI companies or departments within larger organizations. You can also network with professionals in the field and attend industry events to increase your chances of finding job openings.
The Future of AI Career Paths
The artificial intelligence industry is in the middle of a boom. According to recent data, the market size was $95.60 billion in 2021. However, by 2030, the market size is forecasted to reach $1.8 trillion, growing at a stunning CAGR of 32.9%.
This growth will drive AI companies and other organizations to look for additional support. According to the Bureau of Labor Statistics, computer and information technology jobs will increase by 15% between now and 2031. This is much faster than average growth when compared to all other occupations.
Job opportunities range from those specific to AI to those specific to data and machine learning. Due to the nature of AI and its complexities, there are virtually endless career paths to choose from.
Frequently Asked Questions (FAQs)
Is AI a Good Career?
AI is a highly promising and lucrative career field with a growing demand for skilled professionals. With advancements in technology and the increasing integration of AI in various industries, pursuing a career in AI can lead to numerous opportunities for growth and development.
What Skills Do You Need To Land an Entry-Level AI Position?
To land an entry-level AI position, you typically need skills in programming languages such as Python, R, Java, or C++, as well as knowledge of data structures, algorithms, and machine learning concepts. Strong analytical and problem-solving abilities, as well as a solid understanding of statistics, are also important for success in AI roles.
Which Industries Hire AI Professionals?
AI professionals are in demand across a wide range of industries, including but not limited to healthcare, finance, retail, manufacturing, automotive, and technology.
The Bottom Line: AI Career Opportunities are Growing
As the AI industry continues to grow, so will the opportunities for a highly successful career as an AI professional. While AI leverages software and hardware to perform its highly technical work, humans must still be the masterminds behind it. If you’re considering a new career path in tech, a career in AI might be an exceptionally rewarding fit.
For a full portrait of the AI vendors serving a wide array of business needs, read our in-depth guide: 150+ Top AI Companies 2024