Top 10 AI Careers
The AI revolution presents an unprecedented chance for advancement and creativity, rendering a career in AI highly gratifying. With sectors ranging from healthcare to space exploration adopting AI, there is a surging demand for proficient professionals. Becoming an AI expert places you at the forefront of technological progress and unlocks opportunities for diverse and lucrative job roles. What are the Top 10 AI Careers?
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This post outlines the top ten AI careers, illustrating why the present moment is perfect for immersing oneself in this flourishing domain and molding the future. Discover the advantages of securing an AI position and how it can propel your career to unprecedented success.
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Is AI a High Paying Career Option?
The field of Artificial Intelligence (AI) presents a promising career trajectory, evidenced by its substantial job growth, which has surged by 32% in recent years. Moreover, a noticeable talent gap underscores the high demand for proficient professionals. From engineers to researchers and specialists in natural language processing, AI roles offer generous salaries, averaging over $100,000. This reflects the industry's esteemed value and potential for significant financial rewards.
Furthermore, the AI sector provides growth opportunities and flexibility, enabling professionals to engage in various capacities such as freelancing, consulting, or product development. Additionally, the skills acquired in AI are transferrable across multiple industries, rendering it a versatile and appealing career choice for aspiring individuals.
AI Careers: Diverse Opportunities Await
While artificial intelligence (AI) is a relatively new and specialized field, its careers are far from uniform. AI encompasses many job roles, requiring distinct skills and experiences to excel.
Machine Learning Engineer
These professionals straddle data science and software engineering realms, constructing scalable data models for analyzing vast datasets. Skills in programming, machine learning, and deep learning are crucial.
Average Salary: $131,000
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.
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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 you 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.
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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.
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Data Scientist
Experts in transforming raw data into actionable insights, leveraging technology and algorithms for analysis. Advanced degrees and proficiency in programming and statistical tools are prerequisites.
Average Salary: $105,000
Data scientists collect raw data, analyze it, and glean insights for various purposes. They use different 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 as 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.
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Business Intelligence Developer
These specialists process and analyze complex data to uncover trends, designing and maintaining data platforms for dashboards. Engineering or computer science backgrounds and proficiency in data warehouse design and BI technologies are essential.
Average Salary: $87,000
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.
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However, unlike analysts, business intelligence developers don’t create the 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:
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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, which increases to an average of $130,000 with experience.
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Research Scientist
Focused on advancing AI through innovative inquiries, they excel in mathematics, machine learning, and statistics. Often holding doctoral degrees, they possess expertise in computer perception and natural language processing.
Average Salary: $100,000
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.
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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.
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Research scientists are in high demand and command an average salary of $99,800, although the average salary may vary.
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Big Data Engineer/Architect
These professionals create systems facilitating communication between diverse business areas and technologies, often working with Hadoop and Spark systems. Skills in programming, data mining, and visualization are essential.
Average Salary: $151,000
Prominent 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.
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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. Prominent data engineers are expected to have C++, Java, Python, or Scala programming skills. They also need to have experience in data mining, data visualization, and data migration.
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Prominent data engineers are among the best-paid roles in artificial intelligence, with an average salary of $151,300. Your average wage may vary across industries, though.
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Software Engineer
I specialize in crafting software for AI applications and merging development tasks with AI-specific needs like continuous integration. A blend of software engineering prowess and AI knowledge is required.
Average Salary: $105,000
AI software engineers build software products for AI applications. They combine development tasks like writing code, continuous integration, quality control, API management, etc., for AI tasks. They also develop and maintain the software that data scientists and architects use. They stay informed and updated about new artificial intelligence technologies.
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An AI software engineer is expected to be skilled in software engineering and artificial intelligence. They need to have programming skills as well as statistical/analytical skills. Companies typically seek a bachelor’s degree in computer science, engineering, physics, mathematics, or statistics. Certifications in AI or data science help land a job as an AI software engineer.
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The average salary of a software engineer is $108,000, but depending on specialization, experience, and industry, it can be as high as $150,000.
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Software Architect
Focused on designing and maintaining systems and platforms for AI, requiring a blend of educational qualifications and practical experience in areas like cloud platforms and data processes.
Average Salary: $150,000
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.
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AI-driven companies expect software architects to have at least a bachelor’s degree in computer science, information systems, or software engineering. In a practical role, experience is as necessary as educational qualification. Hands-on experience with cloud platforms, data processes, software development, statistical analysis, etc., will place you in good stead.
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Software architects earn an average salary of $150,000. Your average wage can increase significantly with expertise in artificial intelligence, machine learning, and data science.
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Data Analyst
These professionals prepare data for machine learning models and craft insightful reports, necessitating SQL, Python, analytics dashboards, and business intelligence skills.
Average Salary: $65,000
For a long time, the data analyst was someone who collected, cleaned, processed, and analyzed data to glean insights. These tasks were mostly mundane and repetitive. With the rise of AI, much of the mundane work has been automated. Therefore, the 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.
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As a result, an AI data analyst needs to know more than just spreadsheets. They need to be skilled in:
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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 average salary for data analyst roles.
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Robotics Engineer
Innovating and maintaining AI-powered robots, these engineers require advanced degrees and knowledge in CAD/CAM and machine learning.
Average Salary: $87,000
The robotics engineer is perhaps 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.
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Robotics engineers build and maintain AI-powered robots. Organizations typically expect advanced degrees in engineering, computer science, or similar 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.
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The average salary of a robotics engineer is $87,000, but with experience and specialization, it can increase to $130,000.
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NLP Engineer
Specializing in human language technology, these engineers develop voice assistants and speech recognition systems, necessitating expertise in computational linguistics and programming languages like Python.
Average Salary: $78,000
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. Organizations expect a specialized degree in computational linguistics for the role of an NLP engineer. They might also be willing to consider applicants with computer science, mathematics, or statistics qualifications.
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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.
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The average salary of an NLP engineer is $78,000, going up to an average wage of over $100,000 with experience.
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What Skills Do You Need To Land an Entry-Level AI Position?
While not all AI positions are the same, some commonalities regarding entry-level requirements exist. 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.
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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, and 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 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 ensure their foundational skills are covered.
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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 sector 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.
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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 hiring.
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FAQs About Careers in AI
Are AI Jobs in High Demand?
The current job outlook for artificial intelligence (AI) 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 attract candidates.
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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 if not 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.
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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.
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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, Information Technology, or any other engineering degree. When applying for entry-level positions, closely examine the skills required. Do you need a Master’s Degree, or do you already have the right skills and knowledge to pursue the role? You can work in the field without studying further if you have the right technical, communication, and problem-solving skills – with a portfolio to back you up.
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