Key takeaways
- Top jobs in AI include roles like:
- Artificial intelligence (AI) engineer
- Machine learning engineer
- Data engineer
- Robotics engineer
- Software engineer
- Data scientist
- Database Architects
- Natural language processing engineer
- AI research scientist
- Computer vision engineer
- Big data engineer
- Data analyst
- Technology risk manager
- Deep learning engineer
- Transcriptionist
- Cybersecurity specialist
- Business intelligence developer
- Freelance AI Trainer
- Prompt engineer
- AI Content Specialist
- AI Model medical trainer
- Four major career paths in AI include:
- Machine learning engineer with an average salary of $149,864 per year
- AI researcher with an average salary of $123,959 per year
- NLP engineer with an average salary of $121,755 per year
Top four jobs in AI
Here is a detailed overview of the top four AI career paths and subfields that you can explore.
Machine learning engineer duties
Average salary: $149,864 per year (ZipRecruiter)
Machine learning or ML is all about the intersection point between data science and software engineering. Every AI engine you use, such as ChatGPT, which provides responses and recommendations, is developed and trained by ML engineers.
As the job title suggests, machine learning is focused on training and preparing advanced models to use and understand large sets of data automatically. So, from building to training these models, ML engineers are at the core of it all. Here is a list of machine learning engineer duties:
- Build models that recognize and understand data to generate responses
- Use algorithms like regression, decision trees, neural networks, and deep learning
- Train and manage algorithms to improve reliability
- Collect, manage, and organize large data sets
- Develop testable models and develop them to large-scale functional models
- Ensure models run efficiently in real-world applications
- Deploy advanced algorithms and ensure effective functionality
- Retrain or update models as data changes, called model drift
- Work closely with data scientists, software engineers, and product managers
- Provide effective solutions to business problems related to ML and technology
So, the key skills required for ML engineering jobs are:
- Strong programming and software engineering skills
- Solid understanding of math including linear algebra and more
- Knowledge of machine learning algorithms
- Problem-solving and analytical thinking
AI researcher role
Average salary: $123,959 per year (ZipRecruiter)
With a continuously growing technological field such as Artificial Intelligence, professionals are expected to keep up with the industry trends and emerging technologies. Therefore, research sits at the core of it all, making it necessary for AI specialists to have ample research skills.
So, an AI researcher focuses on creating new artificial intelligence methods and advancing the science behind AI, rather than just applying existing models. Their goal is to push the boundaries of what AI systems can do.
Therefore, they do not work hands-on with the development of new AI models and systems. Instead, they have a very important role to play at the backend, making suggestions driven by data. However, some AI research specialists definitely need to test, optimize, and give feedback on new AI models.
So, some important tasks and responsibilities played by AI researchers are:
- Invent or improve machine learning, deep learning, and reasoning algorithms
- Run scientific research on controlled experiments and analyze statics using mathematical methods
- Work on areas like reinforcement learning, computer vision, NLP, and generative AI
- Explore AI safety, alignment, and ethics
- Design experiments to test new ideas and hypotheses
In addition to this, AI researchers are also expected to work closely with seniors members of an organization. Their interaction typically involves giving research findings and reports that contribute towards AI models and frameworks.
Moreover, AI research roles are found in tech labs, research institutes, and tech hubs like Meta and Google. Some of the key skills required are:
- Programming
- Advanced mathematics and statistics
- Critical thinking to aid hypothesis testing and more
- Use relevant research methodology and tools
- Fundamental ML knowledge
NLP engineer job description
Average salary: $121,755 per year (ZipRecruiter)
Many people often confuse ML with natural language processing jobs. However, both are very different – although focused on AI models and their functionality. ML engineers are focused on training AI algorithms and models to use and understand data and transcribe it into functional prompts.
On the flipside, NLS engineers are focused on training AI models to learn and understand human languages, and interpret them, particularly using text to speech functionality.
In essence, NLP engineer jobs are focused on powering AI models such as chatbots, voice assistants, search engines, translation tools, and text-analysis systems. Both verbal and written human languages are the primary focus of NLP experts, depending on the NLP engineer job description and requirement.
One of the most important roles played by today’s NLP engineers is to keep AI models up to date with changing or evolving languages. Every day, new social media lingo or slang surfaces. These make a crucial part of not only human-to-human interaction but also human-to-AI interactions. Therefore, NLP engineers are expected to keep up with the trends and retrain models accordingly.
So, some of the most important tasks and responsibilities of NLP engineers are:
- Develop models for text classification, summarization, translation, and question answering
- Clean, tokenize, and normalize large volumes of text
- Handle unstructured data like emails, chats, documents, and social media
- Fine-tune large language models (LLMs) for specific tasks or industries
- Optimize latency, memory usage, and scalability
- Continuously retrain models as language evolves
AI ethics careers
Average salary: $132,608 per year (ZipRecruiter)
When AI first became available to the common public, such as tools like Grok and ChatGPT, a lot of debate surrounded the implications of AI. Even now, the implications of AI, such as its impact on certain jobs, is still a hot topic that is still passionately discussed.
So, the intensity of discussion surrounding AI and its implications tells us that ethical considerations are a huge part of it all. Therefore, AI ethics careers are legitimate and crucial for the efficient deployment and development of AI models.
In this capacity, AI ethicists are not only high in demand, but also essential for most tech hubs and research labs. To be specific, AI Ethicists ensure that artificial intelligence systems are fair, transparent, safe, and aligned with human values. Their job is to identify ethical risks in AI and guide organizations to build and use AI responsibly.
Moreover, AI ethicists play a vital role in detecting so many important issues that can occur in AI tools, such as biases, discrimination, inaccurate information, and any possible misuse even from the user’s end. Additionally, AI ethics specialists work closely at every stage, such as AI model development, deployment, training, and oversight.
Another key role played by AI ethicists is to manage ethical issues like plagiarism. Additionally, they also focus on ensuring data privacy, which is a huge concern in today’s increasing reliance on technology. To build AI ethics careers, you can get a degree in various majors such as computer science, cybersecurity, and AI specializations.
Here is a list of common AI ethics job tasks and responsibilities:
- Detect bias, discrimination, and unfair outcomes in AI models
- Create ethical frameworks and principles for AI development
- Help define policies around transparency and other ethical considerations
- Audit datasets and algorithms for bias or harmful behavior
- Review high-stakes AI systems, specifically in industries like healthcare and fintech
- Collaborate with engineers, data scientists, legal teams, and leadership
- Translate ethical concerns into practical design
- Assess risks related to privacy, surveillance, and misuse
List of common jobs in AI for bachelor’s degree holders
While careers in NLP, ML, or AI ethics are the most common and popular paths, there are some other AI job roles you might want to explore. With a bachelor’s degree in AI, many job roles and titles open up, thanks to advanced coursework that helps develop new skills and capabilities.
So, when you are planning for college and trying to pick the best college major for yourself, you should take a look at the various types of AI jobs that you may become eligible for, along with the possible salary outlook. Let’s have a look!
| Entry-level AI-related jobs |
| Big data engineer |
| Data analyst |
| Technology risk manager |
| Deep learning engineer |
| Transcriptionist |
| Cybersecurity specialist |
| Business intelligence developer |
| Freelance AI Trainer |
| Prompt engineer |
| AI Content Specialist |
| AI Model medical trainer |
Here are top-paying AI engineer jobs and more:
|
Top-paying AI jobs |
Average annual salary |
| Artificial intelligence (AI) engineer | $149,000 |
| Machine learning engineer | $159,000 |
| Data engineer | $131,000 |
| Robotics engineer | $141,000 |
| Software engineer | $148,000 |
| Data scientist | $153,000 |
| Database Architects | $123,100 |
| Natural language processing engineer | $113,000 |
| AI research scientist | $192,000 |
| Computer vision engineer | $162,000 |
Note: Data is as of March 2026.
Colleges offering AI degrees for a professional career
Whichever career path you choose as an AI professional or specialist, keep in mind that these jobs require expertise, knowledge, and technical skills. Moreover, most entry-level jobs require a minimum of a bachelor’s degree to hire anyone for NLP, ML, or AI researcher jobs.
So, you should take a look at a comprehensive list of colleges and universities offering AI bachelor’s degrees, such as:
College name |
Program |
Tuition |
| Princeton University | Bachelor of Arts (AB) or Bachelor of Science in Engineering (BSE) | $68,140 (source) |
| Massachusetts Institute of Technology | Artificial Intelligence and Decision Making | $32,155 per academic year (College COA) |
| Stanford University | B.S. in Symbolic Systems with an AI concentration | $22,577 per quarter (College COA) |
| University of Illinois, Urbana-Champaign | B.S. in Computer Science | Illinois resident: $18,046-$23,426
Non-resident: $38,398-$46,498 (source) |
| University of Texas-Austin | Machine Learning & Artificial Intelligence Concentration | In-state: $10,858-$13,576 per year Out-of-state: $38,650-$46,498 per year
(Source) |
Ohio University |
Artificial Intelligence, B.S | In-state: $14,582 per year
Out-of-state: $25,796 per year (source) |
| Columbia University | Artificial Intelligence Minor | 2025-2026 academic year costs update |
| Arizona State University | Bachelor of Science in Artificial Intelligence in Business | In-state: $13,534 Out-of-state: $37,072 (source) |
| Rhode Island College | Bachelors in AI | In-state: $5,053 per semester Out-of-state: $13,333 per semester (source) |
| Keiser University | Artificial Intelligence BS Degree | $39,189 per year (US News) |
| Boise State University | Bachelor of Science in AI Science | In-state: $9,364 per academic year
Out-of-state: $28,478 per academic year (Source) |
| Illinois Institute of Technology | Bachelor of Science in Artificial Intelligence | $51,648 per academic year (source) |
| Capitol Technology University | Bachelor of Science (BS) in Artificial Intelligence | $13,635 for academic years 2026-2027 (source) |
| Dakota State University | Artificial Intelligence, BS | In-state: $9,084 per year Out-of-state: $12,276 per year (source) |
| Oakland University | Bachelor of Science in Artificial Intelligence | $590.50 per credit hour (source) |
| Marymount University | Artificial Intelligence (B.S.) | $41,236 per year for full-time enrollment (source) |
Note: Data is as of March 2026.
Final thought
In summary, there are many interesting career paths and fields you can explore once you have a degree in AI. However, keep in mind that AI degrees are essential for all entry-level AI jobs, especially for beginners. Moreover, jobs like NLP and ML specialists are all tied together, with ia ethics careers being one of the more diverse fields. So, a bachelor’s in AI, computer science, or data science can help you start your AI career.
Frequently Asked Questions
What jobs are getting created because of AI?
Many people feared that AI will replace several jobs, such as content writing and accountant jobs. However, the reality is really the opposite, with AI significantly birthing many new job roles across various industries such as healthcare and finance. So, some of the newest jobs getting created by AI include:
- Prompt engineer
- AI ethicist
- ML engineer
- NLP engineer
- Computer vision engineer
- Robotics engineer
- AI product manager
- AI automation
- AI support specialist
- AI trainer
- AI strategist
What jobs will AI replace by 2030?
It is misleading to say that AI will replace some jobs altogether. However, there may be reduced reliance on human employees to perform certain roles. Moreover, it is difficult to say what jobs exactly will be replaced or reduced by the advancement of AI by the year 2030. However, some clerical roles and other redundant jobs may be replaced by AI, such as:
- Admin support
- Customer support
- Retail cashiers
- Manufacturing employees
- Data entry roles
- Front desk roles
- Proofreader roles
- Bookkeeping roles
- Warehouse laborers
- Bank teller roles
How to get a job in AI?
It is very much possible to get a job in AI if you follow the right path and make informed choices. Firstly, AI is a broad field where several subfields and career paths are involved. Therefore, start with choosing a specific specialization track or focus career path. Selecting this path early on can help you choose your qualification easily, such as getting a degree in AI ethics or AI security. Some options included are:
- Machine learning
- AI ethics
- Data science
- AI research
- Programming
Next, to get a job in AI, you need to develop core skills either through certification courses or a bachelor’s degree. Keep in mind that certification courses help you develop essential skills, but a bachelor’s degree is one qualification that is required for entry-level jobs. You can get a bachelor’s in AI from any of the top colleges for a bachelor’s in AI. You can get a degree in computer science, AI, or data science bachelor’s.
Furthermore, you can start your career as an AI specialist through short-term employment such as internships and apprenticeships. Lastly, make use of online job boards to not only build your professional network but also find relevant AI jobs.