Important points
Entry-level artificial intelligence jobs span a variety of roles across industries such as agriculture, finance, healthcare, and IT.
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Entry-level AI roles include positions such as AI Research Assistant, Machine Learning Intern, Data Analyst, Junior Data Scientist, AI Software Developer, NLP Intern, Computer Vision Intern, and AI Product Support Specialist.
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Some entry-level AI positions, such as AI Product Support Specialist, only require a high school diploma and relevant IT certification, while others may require a bachelor’s or advanced degree.
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Build the programming skills, machine learning knowledge, and data analysis knowledge typically required for these roles before you step into the field.
Read below for a breakdown of the average salary, job outlook, and qualifications for each role. If you’re ready to jumpstart your career in AI, consider enrolling in Gemini for Developers Specialization. In just one month, you can build essential skills for AI software development, including token management, AI agent architecture and deployment, and strategic model selection.
What are entry-level AI jobs?
Entry-level AI jobs require less experience than more advanced AI jobs. Starting at entry level is a good way to move on to a senior level position in a related field. Entry-level AI professionals work in a variety of industries and fields, including:
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agriculture
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finance
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government
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health care
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information technology
The exact nature of the entry-level AI job you take will depend on whether you want to focus on developing algorithms, improving machine learning and language processing, or implementing AI in practical ways, such as programming complex sensors in advanced robots.
Entry-level AI jobs and salaries
The options range from working on AI projects in an academic setting to creating AI software. Check out some potential entry-level AI jobs, their salaries and job prospects, and the requirements needed to land them.
How will AI impact entry-level jobs?
AI is transforming entry-level jobs, making it increasingly important for early career candidates to use these tools judiciously. Rather than using AI for every task, job seekers can benefit more by knowing when to use AI, how to critically evaluate its results, and when independent judgment is still needed. In this context, staying competitive is not only about getting used to AI and using it in ways that support rather than replace one’s own reasoning and development. Workplace skills such as communication, problem solving, and research will continue to be invaluable across industries.
AI research assistant
Average annual income in the US: $87,000-$137,000 [1]
Employment outlook (growth forecast from 2024 to 2034): 20% [2]
requirements: Master’s degree in Computer Science. However, a bachelor’s degree may be enough for a government position.
AI research assistants often work in university settings. They assist with AI-related projects under the supervision of experienced AI engineers or professors. In this position, you will help collect and analyze data to help develop and perfect machine learning algorithms that produce better AI output.
machine learning intern
Average annual income in the US: $108,000-$171,000 [3]
Employment outlook (growth forecast from 2024 to 2034): 36% [4]
requirements: Bachelor’s degree in data science or related field. You can do an internship while earning your degree. Coursework in statistics or computer science can also be helpful, as can coding certifications.
Under the supervision of professional engineers, machine learning interns develop the code that enables AI to work in the first place. As a machine learning intern, you may not be able to write code from scratch. You can test or debug according to your supervisor’s instructions.
data analyst
Average annual income in the US: $72,000-$122,000 [5]
Employment outlook (growth forecast from 2024 to 2034):34% [4]
requirements: Bachelor’s degree in computer science, statistics, or information systems and knowledge of SQL, Python, and R.
Data analysts collect, clean, analyze, and report data in a variety of fields. This job primarily involves identifying trends and patterns in data. We also share insights with stakeholders through reports and visualizations to help stakeholders and managers make more informed, data-driven decisions.
junior data scientist
Average annual income in the US: $118,000-$197,000 [7]
Employment outlook (growth forecast from 2024 to 2034):34% [4]
requirements: Bachelor’s degree in mathematics, statistics, computer science, or related field. In some cases, a master’s degree or doctoral degree.
Junior Data Scientists help explore and analyze data that goes into machine learning programs. As a Junior Data Scientist, your goal is to discover patterns in unstructured data and learn how to use them to create solutions based on that data.
AI software developer
Average annual income in the US: $123,000-$185,000 [8]
Employment outlook (growth forecast from 2024 to 2034):15% [9]
requirements: Bachelor’s degree in Computer and Information Technology or related field.
AI software developers often use computer languages such as R, Java, and Python to create new AI software. However, you can also work with an existing code network instead of writing code from scratch. This role often requires exploring data generated by AI models and workshopping AI training modalities to improve chatbot output.
Natural Language Processing (NLP) Intern
Average annual income in the US: $108,000-$171,000 [10]
Employment outlook (growth forecast from 2024 to 2034): 20% [2]
requirements: Bachelor’s degree or certificate in engineering, data science, or computer science. In some cases, a master’s degree or doctoral degree.
The Natural Language Processing (NLP) intern works with NLP engineers to teach AI how to better understand human language, both input and output, so it can provide more authentic and human-like answers. NLP is the primary machine learning modality behind generative AI, one of the most popular applications of AI technology today.
computer vision intern
Average annual income in the US: $119,000-$184,000 [11]
Employment outlook (growth forecast from 2024 to 2034): 20% [2]
requirements: Bachelor’s degree in Computer Science or Information Technology. Coding skills and knowledge of deep learning libraries.
Computer vision interns help computer vision engineers improve the visual aspects of generative AI. By programming NLP into AI models, computer vision technology enables computers to understand visual (rather than textual) input and output image-based responses to queries in a meaningful way.
AI Product Support Specialist
Average annual income in the US: $66,000-$107,000 [12]
Employment outlook (growth forecast from 2024 to 2034): -3 percent [13]
requirements: High school diploma (possibly associate degree) and related IT certification.
AI Product Support Specialists help users troubleshoot AI-related products. In this entry-level AI job, you can advise potential customers about the value proposition of a particular product and help users decide which option to choose. AI Product Support Specialists may require IT, cybersecurity awareness, and customer service skills to perform well.
Skills and qualifications needed for entry-level AI jobs
These jobs can help you get hired to develop more advanced skills, but typically require you to start with a solid skill set, familiar with AI-related programming languages and machine learning concepts. Qualifications that may be required include:
programming skills
AI professionals usually know at least one coding language fairly well. Common coding languages include:
Understanding machine learning algorithms
Algorithms are at the heart of machine learning. Without these, AI models cannot detect patterns or make predictions based on training data. In other words, machine learning algorithms need to be understood in a fairly sophisticated way before an AI model can be taught in the first place.
Knowledge of data processing and analysis tools
A variety of data processing and analysis tools exist. AI professionals use them to collect, store, analyze, and visualize qualitative and quantitative data. Common such tools include Power BI, Tableau, Erwin, and RapidMiner.
Basic knowledge of statistics and mathematics
Many AI algorithms work with probability-based models, so a background in statistics is helpful. Advanced mathematics and statistics training covers key AI-related concepts related to probability and prediction.
skills at work
Working with AI requires more than advanced technical ability. It is also important to develop workplace skills such as active listening, effective communication, collaboration, and critical thinking. These skills will help you connect with others and integrate into the company culture.
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