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High-Paying AI Jobs & Careers to Pursue in 2024

10 minute read | February 26, 2024
Sakshi Gupta

Written by:
Sakshi Gupta

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The AI revolution offers an unparalleled opportunity for growth and innovation, making a career in AI exceptionally rewarding. As industries from healthcare to space exploration embrace AI, the demand for skilled professionals is soaring. Being an AI professional not only positions you at the forefront of technological advancements but also opens doors to a variety of high-paying, dynamic job roles.

This post highlights the top ten AI careers, showcasing why now is the ideal time to dive into this thriving field and shape the future. Explore the benefits that come with landing an AI job and how it can elevate your career to new heights.

Is AI a Good Career?

Artificial Intelligence (AI) is considered a promising career path due to its significant job growth, with hiring increasing by 32% in recent years, and a notable talent gap indicating a high demand for qualified professionals. AI roles, including engineers, researchers, and specialists in natural language processing, command high salaries, averaging over $100,000, reflecting the industry’s value and potential for financial reward.

The field offers diverse growth opportunities and flexibility, allowing professionals to work in various capacities such as freelancers, consultants, or product developers. Moreover, the skills acquired in AI are transferable across numerous industries, making it a versatile and attractive career choice.

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AI Jobs & Careers

Despite being a new and niche field, careers in artificial intelligence aren’t homogenous. Within AI, there are various kinds of jobs needing specific skills and experience.

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. You will probably need a bachelor’s degree in Computer Science or a related field.

The average salary of a machine learning engineer in the US is $​​131,000. Organizations like Apple, Facebook, Twitter, etc., pay significantly higher—in the average salary range of $170,000 to $200,000. Read more about ML engineer salaries here.

Data Scientist

Data scientists collect raw data, analyze it, and glean insights for a wide range of purposes. They use various 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:

  • A bachelor’s degree
  • 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. With experience, the average salary can go up to $200,000 for a director of data science position.

Business Intelligence Developer

Business intelligence (BI) developers 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 monitoring sales trends to inform distribution strategy.

However, unlike an analyst, business intelligence developers don’t create the reports themselves. 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, going up to an average salary of $130,000 with experience.

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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 in artificial intelligence, including mathematics, machine learning, deep learning, and statistics. Like data scientists, researchers are expected to have a doctoral degree in computer science.

Hiring organizations expect research scientists to have extensive knowledge and experience in computer perception, graphical models, reinforcement learning, and natural language processing. 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, although the average salary may vary.

Big Data Engineer/Architect

Big data engineering professionals and architects develop ecosystems that enable various business verticals and technologies to communicate effectively. Compared to data scientists, this role can feel more involved, as 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 practical role than that of, say, a research scientist or AI engineer, hands-on experience is often treated as a good substitute for a lack of advanced degrees. Big data engineers are expected to have programming skills in C++, Java, Python, or Scala. They also need to have experience in data mining, data visualization, and data migration.

Big data engineers are among the best-paid roles in artificial intelligence, with an average salary of $151,300. Your average salary may vary across industries though.

Software Engineer

AI software engineers build software products for AI applications. They bring together development tasks like writing code, continuous integration, quality control, API management, etc., for AI tasks. They develop and maintain the software that data scientists and architects use. They stay informed and updated about new artificial intelligence technologies.

An AI software engineer is expected to be skilled in software engineering and artificial intelligence. They need to have programming skills as statistical/analytical skills. Companies typically look for a bachelor’s degree in computer science, engineering, physics, mathematics, or statistics. To land a job as an AI software engineer, certifications in AI or data science are helpful too.

The average salary of a software engineer is $108,000. This goes up to an average salary of $150,000 based on your specialization, experience, and industry.

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 their software architects to have at least a bachelor’s degree in computer science, information systems, or software engineering. As a practical role, experience is as important as educational qualification. 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. Your average salary can go up significantly with expertise in artificial intelligence, machine learning, and data science.

Data Analyst

For a long time, the data analyst was someone who collected, cleaned, processed and analyzed data to glean insights. For the most part, these used to be mundane, repetitive tasks. With the rise of AI, much of the mundane work has been automated. Therefore, the analyst role has 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:

  • 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 in excess of $100,000 average salary for data analyst roles.

Robotics Engineer

The robotics engineer is perhaps one of the first of AI careers, when industrial robots were gaining popularity as early as the 1950s. From the assembly lines to teaching English, robotics has come a long way. 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. For such roles, organizations typically expect advanced degrees in engineering, computer science, or similar. 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 an average salary of $130,000 with experience and specialization.

NLP Engineer

Natural Language Processing (NLP) engineers are AI professionals who specialize in human language, including spoken and written information. 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 a qualification in computer science, mathematics, or statistics.

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. Experience with Python, ElasticSearch, web development, etc., could be helpful.

The average salary of an NLP engineer is $78,000, going up to an average salary of over $100,000 with experience.

What Skills Do You Need To Land an Entry-Level AI Position?

While not all AI positions are the same, there are some commonalities when it comes to entry-level requirements. To help better understand what skills, tools, and general requirements are shared across job listings, we asked ChatGPT to analyze a group of AI jobs from companies like OpenAI and Honda and return a list of the most commonly found items.

Here’s what it found:

Skills and Knowledge

  • Understanding of AI/ML concepts and algorithms.
  • Excellent analytical and problem-solving skills.
  • Proficiency in programming languages, especially Python, and possibly R or Java.
  • Experience with machine learning frameworks such as TensorFlow, Keras, PyTorch.
  • Familiarity with data manipulation and analysis tools (SQL, Pandas, NumPy).
  • Knowledge of big data technologies and distributed computing frameworks (e.g., Hadoop, Spark).
  • Experience in scientific software development/analysis.
  • Ability to convey technical concepts to non-technical stakeholders.
  • Strong attention to detail and ability to work with complex data.
  • Experience with natural language processing (NLP), computer vision, or other AI subfields is a plus.
  • Familiarity with cloud-based machine learning platforms (AWS SageMaker, Azure Machine Learning).

Tools

  • Machine Learning Frameworks: TensorFlow, Keras, PyTorch.
  • Data Analysis: SQL, Pandas, NumPy.
  • Big Data Technologies: Hadoop, Spark.
  • Cloud Platforms: AWS SageMaker, Azure Machine Learning.
  • Development Tools: Jupyter Notebook, GitHub for ML Ops.
  • BI Tools: Tableau, PowerBI (for presenting data insights).

General Requirements

  • Bachelor’s degree in Computer Science, Engineering, Physics, Mathematics, or related technical field. Advanced degrees (Master’s, Ph.D.) are preferred for more specialized roles.
  • 1-3 years of experience working in the field of artificial intelligence or machine learning.
  • Excellent verbal and written communication skills.
  • Passion for developing solutions to complex engineering problems.
  • Ability to collaborate effectively with cross-functional teams.
  • Compliance with ethical and legal standards related to data privacy, security, and model bias.

While the above should not be treated as a comprehensive list, it is an excellent checklist for aspiring AI professionals to make sure they have their foundational skills covered.

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. The industry with the most number of 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 also 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 also hiring.

FAQs About Careers in AI

Are AI Jobs in High Demand?

The current Artificial intelligence (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. This will add about 531,200 new jobs in the industry, with a higher than average salary to draw candidates.

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 to have hands-on experience to land a job in AI, even if not exactly 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.

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. Organizations can no longer reject employees without a college degree if they have demonstrable skills and experience in artificial intelligence.

Do You Need an Advanced Degree (Master’s Degree) to Work in AI?

You don’t necessarily need a Master’s Degree, but even entry level jobs may require a Bachelor’s Degree in Computer Science or Information Technology, or any other engineering degree. When applying for entry level positions, take a closer look at the skills required. Do you really need a Master’s Degree or do you already have the right skills and knowledge to pursue the role? If you have the right technical skills, communication skills and problem-solving skills – with a portfolio to back you up – you can work in the field without studying further. 

Since you’re here…Are you interested in this career track? Investigate with our free guide to what a data professional actually does. When you’re ready to build a CV that will make hiring managers melt, join our Data Science Bootcamp which will help you land a job or your tuition back!

About Sakshi Gupta

Sakshi is a Managing Editor at Springboard. She is a technology enthusiast who loves to read and write about emerging tech. She is a content marketer with experience in the Indian and US markets.