Entry-Level AI Jobs: Salaries, Roles, and How to Start in 2025

Samantha Blake – Ex-Amazon Design Recruiter | Interview Coach

May 28, 2025

AMA Career | Entry Level AI Jobs Salary
AMA Career | Entry Level AI Jobs Salary
AMA Career | Entry Level AI Jobs Salary

Why Entry-Level AI Jobs Are Booming

Artificial intelligence is one of the fastest-growing fields, with AI-related jobs increasing by nearly 75 percent over the last four years. As companies continue integrating AI into their operations, demand for skilled professionals is rising. This creates an excellent opportunity for those looking to enter the field through an entry-level AI job.

Employers seek candidates with a strong foundation in AI concepts, data science, and programming. Entry-level AI positions provide hands-on experience, career growth potential, and competitive salaries. This guide explores common entry-level AI roles, salary expectations, and strategies to start a career in AI.


AI Job Market Outlook for Beginners

Artificial intelligence is transforming industries, from healthcare and finance to retail, education, and cybersecurity. The AI industry is expanding rapidly, driven by advancements in machine learning, automation, and data science.

  • The number of AI companies in the United States has doubled since 2017, with nearly 14,000 startups operating in 2022.

  • The global AI market is expected to grow from $515.31 billion in 2023 to over $2 trillion by 2030.

  • AI-related job postings have significantly increased, with many roles offering competitive salaries even at the entry level.

This rapid growth signals strong career prospects for AI professionals, making it an excellent field for those looking to enter the technology sector.

The demand for AI talent is expected to grow for years to come. According to the U.S. Bureau of Labor Statistics, computer and information research jobs—including AI-related roles—are projected to grow by 15 percent between 2019 and 2029.

Entry-level AI salaries vary based on factors such as location, education, industry, and job responsibilities. However, most entry-level AI positions offer above-average pay compared to other technology-related entry-level jobs.

Below is an overview of common entry-level AI jobs, their responsibilities, salary expectations, and education requirements.


7 High-Potential Entry-Level AI Roles and Salaries

1. AI Research Assistant

AI research assistants support AI and machine learning projects in academic institutions, research labs, and companies. This role provides valuable experience in AI model development, data analysis, and neural network training.

Key Responsibilities:

  • Assist with AI and machine learning research projects

  • Work with neural networks and data science models

  • Analyze and process complex datasets

  • Maintain research databases and coordinate project activities

Salary Range: 74,187 to 88,245 (including bonuses)

Education Requirements:

  • Bachelor’s degree in computer science, data science, AI, or a related field

  • Some roles may require a master’s degree or Ph.D.


2. Junior Data Analyst

Data analysts translate numbers and trends into meaningful insights that help businesses make informed decisions. A junior data analyst focuses on data collection, visualization, and reporting.

Key Responsibilities:

  • Collect, clean, and analyze data

  • Use data visualization tools to create reports

  • Identify patterns and business insights

Salary Range: 42,000 to $82,000

Education Requirements:

  • Bachelor’s degree in statistics, data science, economics, or a related field

3. Junior Software Engineer

Junior software engineers assist in designing, developing, and maintaining AI-driven applications and software solutions.

Key Responsibilities:

  • Write, test, and debug code

  • Collaborate with teams to develop AI-powered software

  • Work with programming languages such as Python, Java, and C++

Salary Range: 59,000 to 77,904

Education Requirements:

  • Bachelor’s degree in computer science or software engineering

  • Experience with AI frameworks is a plus

4. Entry-Level AI Data Scientist

Data scientists develop AI and machine learning models to analyze large datasets and generate insights for businesses.

Key Responsibilities:

  • Build machine learning models

  • Perform data analysis and visualization

  • Work with AI frameworks such as TensorFlow and PyTorch

Salary Range: 81,180 to 102,042

Education Requirements:

  • Bachelor’s or master’s degree in data science, AI, or machine learning

5. Entry-Level Information Systems Analyst

Information systems analysts focus on optimizing AI-driven IT infrastructure and cybersecurity solutions.

Key Responsibilities:

  • Monitor AI-based security systems

  • Identify and resolve system vulnerabilities

  • Support software updates and AI-driven system improvements

Salary Range: 55,492 to 60,938

Education Requirements:

  • Bachelor’s degree in computer science, information systems, or cybersecurity

6. Junior AI Programmer

AI programmers develop and optimize AI-based software applications, working closely with engineers and data scientists.

Key Responsibilities:

  • Write, test, and debug AI-related code

  • Develop AI-driven software applications

  • Maintain and optimize AI algorithms

Salary Range: 47,586 to 59,478

Education Requirements:

  • Bachelor’s degree in computer science or AI

  • Experience with programming languages such as Python and Java

7. Junior AI Project Manager

AI project managers coordinate development timelines and ensure the successful execution of AI-related projects.

Key Responsibilities:

  • Manage AI project workflows

  • Coordinate teams of AI engineers and data scientists

  • Oversee project milestones and ensure deadlines are met

Salary Range: 70,000 to 90,000

Education Requirements:

  • Bachelor’s degree in business, project management, or a technical field

  • AI project management certification is an advantage


How to Build Experience (Even Without a Job Offer Yet)

Even for entry-level AI positions, employers often seek candidates with some level of experience or practical skills. Here are some ways to build expertise:

1. AI and Data Science Bootcamps

AI bootcamps provide intensive training in machine learning, data science, and programming. Many bootcamps offer hands-on projects that simulate real-world AI applications.

2. Internships

AI internships provide practical experience and networking opportunities. Many companies, including tech giants and startups, offer AI internships for students and recent graduates.

3. Online Certifications

Platforms such as Coursera, Udacity, and edX offer AI and machine learning certification courses. Certifications from Google, IBM, and Microsoft can enhance job prospects.

4. Open-Source AI Projects

Contributing to AI and data science projects on platforms like GitHub can help demonstrate skills to potential employers.

5. Advanced Degree Programs

A master's degree in AI, machine learning, or data science provides in-depth knowledge and can significantly boost career opportunities.


Crush Entry-Level Interviews with AI Mock Practice

Landing an entry-level AI job requires not only technical skills but also strong interview performance. Many candidates struggle with preparing for AI-related interviews due to the variety of technical questions and role-specific requirements. AMA Career simplifies this process by offering a fully customized, AI-driven interview preparation platform that mimics real-world interview scenarios.

Experience Realistic Interview Scenarios with AI Simulation

What sets AMA Career apart is its hyper-realistic AI interviewer, designed to simulate real interview experiences. The AI interviewer is tailored to the user’s background and position-specific requirements, ensuring candidates get relevant practice for the exact interview rounds they will face. Additionally, users can engage with an AI avatar with vision, allowing for a more interactive and lifelike experience.

Start Your AI Career Today

AI is one of the most promising fields for job seekers, offering high salaries, strong job security, and exciting career growth opportunities. Entry-level AI jobs provide an excellent starting point for those with a background in computer science, data science, or machine learning.

To increase your chances of landing a job in AI, focus on gaining technical skills, completing relevant coursework, and building real-world experience through projects and internships.

Whether you are just starting or looking to transition into AI, now is the ideal time to explore this dynamic and rapidly growing field.


FAQs: Entry-Level AI Jobs, Salaries & Transitions

1. Do entry-level AI jobs require a Master’s degree?

Not necessarily. Many AI roles are open to candidates with strong foundational knowledge in statistics, Python, and ML—even without a graduate degree. Bootcamp and online certificate graduates often qualify for analyst, junior engineer, and AI support roles if they have good project portfolios.

2. Can I apply for an entry-level AI job without a CS degree?

Yes. Candidates with backgrounds in math, economics, or engineering can transition into AI through:

  • Online courses + certifications

  • Completing 2–3 hands-on projects using real data

  • Participating in open competitions like Kaggle

Employers care about practical skill over pedigree in many entry-level positions.

3. How do AI salaries compare to other entry-level tech jobs?

AI jobs consistently offer 15–35% higher starting pay than roles like QA tester, IT support, or general software intern positions. This is due to:

  • High demand for AI/ML skills

  • Value of automation to business operations

  • Short supply of qualified talent

4. What are the most valuable skills for landing an AI job in 2025?

For beginner roles:

  • Python programming (NumPy, Pandas, scikit-learn)

  • SQL for data extraction

  • Basic ML models (linear regression, decision trees, clustering)

  • Git/GitHub for version control

  • Familiarity with cloud platforms like AWS/GCP

Bonus: writing technical blog posts or documentation to showcase communication skills

5. How long does it take to break into AI from scratch?

With no prior coding or math background:
~6–12 months, depending on intensity

  • 2–3 months learning Python and math

  • 3–4 months learning ML theory + building projects

  • 1–2 months preparing a portfolio and practicing interviews