Artificial intelligence jobs are not a new phenomenon, but as the AI market itself is expanding rapidly, so is the AI job market. According to research firm IDC, AI is currently experiencing an annual growth rate of nearly 40%.
Amid these changes, AI jobs are changing and expanding, and AI salaries are soaring. Previous roles were “statistician” or “mathematician,” but now we’re hearing new terms like “data scientist” and “predictive analytics expert.”
The rapid emergence of new AI titles reflects the fact that the cost of cloud computing and storage has become affordable from prohibitively expensive supercomputers, making AI available for mainstream use. The growth of AI companies and the expansion of related technologies such as machine learning has expanded the number of AI jobs.
Similarly, some of the AI algorithms in use today have been around for decades, but until recently, they lacked the amount and richness of data needed to create value. There are many different types of AI jobs and roles available today, some of which simply add “AI” to an existing title (e.g., “AI developer”). Some reflect different aspects of AI (such as “data engineer,” “algorithm developer,” or “machine learning scientist”).
For the purposes of this article, AI job titles, their typical job descriptions, and salary ranges are limited to technical roles.
See also: Advantages and disadvantages of AI
A typical advertisement for AI jobs in today’s rapidly growing field of artificial intelligence.
AI job title
Job seekers and career builders would be wise not to take AI job titles at face value. For example, some companies require data scientist candidates to have a PhD or master’s degree in computer science or statistics, while other organizations accept certain types of experience without a bachelor’s or college degree. Similarly, a “senior” title may require a graduate degree and more experience with some companies than others.
Some of the most popular AI jobs today include:
- AWS Machine Learning Engineer
- machine learning scientist
AI job content
It’s important to read the job posting’s essential requirements to determine if the job is actually a good fit. For example, some AI tech jobs require R. and Some require Python expertise, while others only require R or Python experience.
Job descriptions, including candidate requirements, may vary by industry. For example, PhDs are common in scientific industries such as pharmaceutical companies, so some jobs may require more advanced degrees than organizations operating in other industries, such as advertising.
Another reason to keep an open mind about job descriptions is that the people creating and approving job requisitions may lack the technical expertise to articulate what the organization actually needs. The result can be unrealistic qualifications that even the most popular experts lack.
Below is a sample job description based on an actual job posting. It has been omitted for ease of comparison.
AI developer
job description: Responsible for maintaining, enhancing, and implementing AI solutions.
Required skills:
- AWS or Azure AI services and frameworks
- AI, ML, NLP, REST APIs, libraries, frameworks
- Design, develop, and deploy cloud applications
- Hands-on experience with AI, ML, NLP, and cloud applications.
education: Bachelor of Computer Science
AI engineer
job description: Develop solutions to large-scale problems and bridge the gap between software developers and research scientists.
Required skills:
- ML, DL, NLP, computer vision
- Past definition, coding, and validation testing experience
- Creating test automation scripts
education: Master’s or PhD in Computer Science, AI, ML, or related field.
algorithm developer
job description: Develop algorithms for specific use cases.
Required skills:
- Evaluate and report algorithm performance
education: Bachelor’s degree in Computer Science or equivalent related to the position (e.g., robotics or electrical engineering)
Machine Learning Engineer on AWS or Azure
What you’ll do: Build data models and create very large data sets.
Required skills:
- 3+ years of experience with AWS or Azure services.
- 3+ years of ML and data labeling
- 3+ years of Python or R and Python
- 3-5 years of data management experience
education: Bachelor of Science, Computational Science, Master’s or Ph.D. may be preferred
AWS or Azure Data Scientist
job description: Translate customer requirements into POC and successful solutions.
Required skills:
- 2+ years of data science experience
- ML, NLP, DL, depending on position and client
- Experience with the platform (AWS or Azure) and its services.
education: Master’s degree in computer science or related field
data scientist
job description: Organize structured and unstructured data, build data models, and interpret complex data sets
Required skills:
- ML and/or NLP, DL depending on position
education: Bachelor’s or Master’s degree in Computer Science or equivalent qualification
lead data engineer
job description: Redesign business intelligence processes, design and develop data models, and share expertise throughout the implementation process.
Required skills:
education: BS, Computer Science or equivalent qualification
lead data scientist
job description: We transform our clients’ challenges and goals into successful AI, ML, or DL solutions that meet or exceed expectations. We train junior data scientists.
Required skills:
- R, Python, or both recommended
- POC development and demonstration
- 8+ years of end-to-end analysis including data collection and requirements specification, processing, analysis, ongoing deliverables and presentation.
- Over 8 years of developing, implementing, and using ML models and quantitative methods for prediction and classification.
- 2+ years of relevant professional experience (e.g. NLP)
education: Master’s degree in computer science, statistics, or mathematics. Ph.D. preferred
machine learning scientist
job description: Develop next-generation machine learning technologies that advance the status quo in specific industries.
Required skills:
- Demonstrated deep understanding of ML algorithms and modeling, including supervised, unsupervised, reinforcement learning models, transfer learning, optimization, and probabilistic graphical models.
- Deep experience with Spark or Hadoop and PyTorch or Tensorflow.
- Python and Java, Scala, and/or R
- Experience analyzing data and creating applications in a production environment.
education: PhD in computer science or related field with emphasis on ML, AI, or data mining, or master’s degree and equivalent experience.
AI jobs: additional experience required
For a variety of complex reasons, some AI jobs require additional significant experience, similar to the positions below. The reality is that the field is still new, so the exact amount of experience will largely depend on the individual employer.
NLP Data Developer/Engineer
job description: Apply various NLP techniques in areas such as classification, data/knowledge extraction, disambiguation, and sentiment analysis. Identify and categorize entities in text, such as people, locations, organizations, dates/times, quantities, percentages, and currencies.
Required skills:
- AWS or Azure AI services and frameworks (cognitive, bots)
- AI, ML, NLP, REST APIs, libraries, frameworks
- Design, develop, and deploy cloud applications
Experience level:
- Have been using the target platform (AWS or Azure) for more than 10 years
- 5+ years of development experience
- Hands-on POC experience to prove architectural concepts
- Experience with large and diverse datasets
education: Master’s degree in Computer Science or Computer Information Systems (CIS)
Senior AI Developer
job description: Responsible for maintaining, enhancing, and implementing solutions.
Required skills:
- AWS or Azure AI services and frameworks (cognitive, bots)
- AI, ML, NLP, REST APIs, libraries, frameworks
- Design, develop, and deploy cloud applications
Experience level:
- Over 10 years of software development
- 5+ years of AI, ML, NLP, and cloud application development
education: Bachelor’s degree in computer science or engineering
Senior data scientist
job description: Design and implement cutting-edge solutions across a wide range of domain areas.
Required skills:
- ML, DL, NLP, computer vision, recommendation engines, pattern recognition, large-scale data mining
- Predictive, statistical, and data mining modeling
- Hadoop, Spark, or other big data platform
- Familiar with ML algorithms
education: Bachelor’s or Master’s degree in computer science, engineering, statistics, or mathematics.
AI salary scale
AI-related jobs tend to have very similar compensation ranges, which can be misleading. It may seem strange that people with the same job title can have base compensation that differs by $50,000 or $100,000, but part of the difference has to do with current compensation levels in a given market. For example, jobs in San Francisco and Manhattan tend to pay more than jobs in other metropolitan areas, once cost-of-living differences are taken into account.
Also, the title “senior” does not necessarily translate into compensation, which may seem strange. In medium and large companies, employees with senior positions tend to be compensated more than employees with similar but more junior positions. However, small businesses with smaller budgets may advertise senior titles instead of senior compensation to attract career builders.
Therefore, job seekers should approach the job search with an open mind and research what is available at the time. Candidates also need to be clear about which positions and compensation packages are acceptable. Because sometimes a better title doesn’t mean a higher salary, and vice versa.
The current salary range for the above positions is as follows:
- AI developer: $90,000 – $150,000
- AI Engineer – $130,000 – $210,000
- Algorithm developer – $90,000 – $130,000
- Machine Learning Engineer – $70,000 – $170,000
- Azure or AWS Data Scientist – $85,000 – $160,000
- Data Scientist: $50,000 – $150,000
- Lead Data Engineer: $90,000 – $175,000
- Lead Data Scientist: $125,000 – $195,000
- Machine Learning Scientist: $100,000 – $150,000
- ML Data Developer: $100,000 – $170,000
- Senior AI Developer: $90,000 – $150,000 (high end)
- Senior Data Engineer: $90,000 – $175,000
- Senior Data Scientist: $95,000 – $210,000
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