Careers in Artificial Intelligence, AI
Over the last few years, artificial intelligence (AI) has opened up possibilities for the future. From space exploration to melanoma detection, it is making waves across industries, making impossible things possible.
As a result, there has also been a steady growth in AI careers—LinkedIn puts artificial intelligence practitioners among the ‘jobs on the rise’ in 2022. This blog post explores the ten excellent and high-paying AI careers you can pursue in 2023 and beyond.
Is Artificial Intelligence a Good Career?
- AI jobs are plenty, with hiring growing by 32% in the last couple of years
- There is a high talent gap—not enough qualified applicants for vacant positions
- AI professionals earn top salaries, well north of $100,000
- As a rapidly evolving industry, growth opportunities in AI careers are diverse
- AI careers are flexible—you could be freelancers, consultants, researchers, practitioners, or even build your own AI products.
What’s the Current AI Job Outlook
The current AI job outlook is quite promising. The US Bureau of Labor Statistics expects computer science and information technology employment to grow 11% from 2019 to 2029, adding about 531,200 new jobs in the industry. This figure, it appears, is a conservative estimate. ‘AI and Machine Learning Specialists’ is the second on the list of jobs with increasing demand, per the World Economic Forum.
AI jobs will grow in number, complexity, and diversity as the industry matures. Thus, this will open doors for various professionals—junior and senior researchers, statisticians, practitioners, experimental scientists, etc. As a result, the outlook for ethical AI is also looking up.
What AI Careers Can You Pursue?
Despite being a new and niche field, careers in artificial intelligence aren’t homogenous. Within AI, various kinds of jobs need specific skills and experience. Let us look at the top ten one by one.
1. Machine Learning Engineer
Machine learning engineers are at the intersection of software engineering and data science. They leverage big data tools and programming frameworks to create production-ready scalable data science models that can handle terabytes of real-time data.
Machine learning engineer jobs are best for anyone with a background that combines data science, applied research, and software engineering. AI jobs seek applicants with strong mathematical skills, experience in machine learning, deep learning, neural networks, and cloud applications, and programming skills in Java, Python, and Scala. It also helps to be well-versed in software development IDE tools like Eclipse and IntelliJ.
The average salary of a machine learning engineer in the US is $1,31,000. However, organizations like Apple, Facebook, Twitter, etc., pay significantly higher—$170,000 to $200,000. Read more about ML engineer salaries here.
2. Data Scientist
Data scientists collect, analyze, and glean insights for various purposes. They use technology tools, processes, and algorithms to extract knowledge from data and identify meaningful patterns; this could be as basic as identifying anomalies in time-series data or complex as predicting future events and making recommendations. The primary qualifications expected of a data scientist are an advanced degree in statistics, mathematics, computer science, etc.
- Understanding of unstructured data and statistical analysis
- Experience with cloud tools like Amazon S3 and the Hadoop platform
- Programming skills with Python, Perl, Scala, SQL, etc.
- Working knowledge of Hive, Hadoop, MapReduce, Pig, Spark, etc.
- The average salary of a data scientist is $105,000. However, with experience, this can go up to $200,000 for a director of data science position.
3. Business Intelligence Developer
Developers of business intelligence (BI) process complex internal and external data to identify trends. For instance, in a financial services company, this could be someone monitoring stock market data to help make investment decisions. In a product company, this could be someone watching sales trends to inform distribution strategy.
However, unlike data analysts, business intelligence developers don’t create reports. They are typically responsible for designing, modeling, and maintaining complex data in highly accessible cloud-based data platforms for business users to use the dashboards. The qualifications expected of a BI developer are:
- Bachelor’s degree in engineering, computer science, or a related field
- Hands-on experience in data warehouse design, data mining, SQL, etc.
- Familiarity with BI technologies like Tableau, Power BI, etc.
- Strong technical and analytical skills
- Business intelligence developers earn an average salary of $86,500, up to $130,000, with experience.
4. Research Scientist
The research scientist role is one of the most academically-driven AI careers. They ask new and creative questions to be answered by AI. They are experts in multiple disciplines of artificial intelligence, including mathematics, machine learning, deep learning, and statistics. Researchers expect to have a doctoral degree in computer science, like data scientists.
Hiring organizations expect research scientists to have extensive knowledge and experience in computer perception, graphical models, reinforcement learning, and natural language processing. In addition, knowledge of benchmarking, parallel computing, distributed computing, machine learning, and artificial intelligence are a plus.
Research scientists are in high demand and command an average salary of $99,800.
5. Big Data Engineer/Architect
Big Data engineers and architects develop ecosystems that enable various business verticals and technologies to communicate effectively. This role can feel more involved than data scientists, as Big Data engineers and architects typically are tasked with planning, designing, and developing Big Data environments on Hadoop and Spark systems.
Most companies prefer professionals with a Ph.D. in mathematics, computer science, or related fields. However, as a more valuable role than a research scientist, hands-on experience is a good substitute for the need for advanced degrees. For example, Big Data engineers expect to have programming skills in C++, Java, Python, or Scala. They also need to have experience in data mining, visualization, and migration.
Big Data engineers are among the best-paid roles in artificial intelligence, with an average salary of $151,300.
6. Software Engineer
AI software engineers build software products for AI applications. They combine development tasks for AI tasks like writing code, continuous integration, quality control, API management, etc. They develop and maintain the software that data scientists and architects use. In addition, they stay informed and updated about new artificial intelligence technologies.
An AI Software Engineer expects to be skilled in software engineering and artificial intelligence. In addition, they need programming and statistical/analytical skills. Companies typically seek a bachelor’s degree in computer science, engineering, physics, mathematics, or statistics. An AI or data science certification is also helpful to land a job as an AI software engineer.
The average salary of a software engineer is $108,000; this goes up to $150,000 based on your specialization, experience, and industry.
7. Software Architect
Software architects design and maintain systems, tools, platforms, and technical standards. AI software architects do this for artificial intelligence technology. They create and maintain AI architecture, plan and implement solutions, choose the toolkit, and ensure a smooth data flow.
AI-driven companies expect software architects to have at least a bachelor’s degree in computer science, information systems, or software engineering. However, experience is as necessary as an educational qualification in a functional role. Hands-on experience with cloud platforms, data processes, software development, statistical analysis, etc., will place you in good stead.
Software architects earn an average salary of $150,000. However, your salary can increase significantly with expertise in artificial intelligence, machine learning, and data science.
8. Data Analyst
The data analyst collected, cleaned, processed, and analyzed data for insights. For the most part, these used to be mundane, repetitive tasks. However, with the rise of AI, much of the everyday work has been automated. Therefore, the data analyst role has been upgraded to join the new set of AI careers. Today, data analysts prepare data for machine learning models and build meaningful reports based on the results.
As a result, an AI data analyst needs to know more than just spreadsheets. They need to be skilled in the following:
- SQL and other database languages to extract/process data
- Python for cleansing and analysis
- Analytics dashboards and visualization tools like Tableau, PowerBI, etc.
- Business intelligence to understand the market and organizational context
- A data analyst earns an average salary of $65,000. However, high-technology companies like Facebook, Google, etc., pay more than $100,000 for data analyst roles.
9. Robotics Engineer
The robotics engineer was one of the first AI careers when industrial robots gained popularity as early as the 1950s. Robotics has come a long way, from the assembly lines to teaching English. Healthcare uses robot-assisted surgeries. Humanoid robots are being built to be personal assistants. A robotics engineer’s job is to make all this and more happen.
Robotics engineers build and maintain AI-powered robots. Organizations typically expect advanced engineering, computer science, or similar degrees for such roles. In addition to machine learning and AI qualifications, robotics engineers might also be expected to understand CAD/CAM, 2D/3D vision systems, the Internet of Things (IoT), etc.
The average salary of a robotics engineer is $87,000, which can go up to $130,000 with experience and specialization.
10. NLP Engineer
Natural Language Processing (NLP) engineers are AI professionals who specialize in human language, including spoken and written information. For example, the engineers who work on voice assistants, speech recognition, document processing, etc., use NLP technology. For the role of an NLP engineer, organizations expect a specialized degree in computational linguistics. They might also be willing to consider applicants with computer science, mathematics, or statistics qualifications.
In addition to general statistical analysis and computational skills, an NLP engineer would need skills in semantic extraction techniques, data structures, modeling, n-grams, a bag of words, sentiment analysis, etc. In addition, experience with Python, ElasticSearch, web development, etc., could be helpful.
The average salary of an NLP engineer is $78,000, going up to over $100,000 with experience.
Which Industries Are Hiring AI Professionals?
There are over 15,000 jobs in AI listed on LinkedIn today. Organizations across a wide range of industries are hiring. However, the industry with the most open AI careers appears to be technology, with companies like Apple, Microsoft, Google, Facebook, Adobe, IBM, Intel, etc., hiring for AI roles.
Closely following this are consulting majors such as PWC, KPMG, Accenture, etc. Healthcare organizations are hiring more—GlaxoSmithKline has multiple open AI-related positions. Retail players like Walmart and Amazon and media companies like Warner and Bloomberg are engaging.
AI Careers FAQs
Can You Get Into AI With No Experience?
As a practical field, the defining factor of an AI professional is their ability to execute projects; this can only come from experience. So, you need hands-on experience to land a job in AI, even without corporate work experience. For instance, Springboard’s Data Science Career Track includes 14 real-world projects to get you comfortable with applying AI to business challenges.
What Skills Do You Need To Land an Entry-Level AI Position?
Not all AI positions are the same. As the list above shows, different roles need different skills/experiences. However, nearly all entry-level roles will expect the following:
- Graduate degree in computer science, mathematics, or statistics
- Familiarity with Python and SQL
- Knowledge of data analysis, processing, and visualization
- Understanding of cloud technologies
- Business understanding about the industry, market, competition, etc.
- Do You Need a Degree To Work in Artificial Intelligence?
- Most job descriptions online will expect at least a bachelor’s degree. However, as we mentioned above, the talent gap is growing. Therefore, organizations can no longer reject employees without a college degree if they have demonstrable skills and experience in artificial intelligence.
How To Work in Artificial Intelligence?
A career in AI is unlike most technology jobs that are available today. As an evolving field, AI jobs demand professionals stay informed of advancements and update themselves regularly. It is no longer enough to gain skills; AI/ML professionals must periodically track the latest research and understand new algorithms.
Moreover, AI is coming under immense social and regulatory scrutiny. As a result, AI professionals need to look beyond just the technical aspects of AI and pay attention to its social, cultural, political, and economic impact.