BestOnlineCollege.org is an advertising-supported website. Many of the school and program listings that appear on this site are from partners who compensate us, and this compensation may affect how, where, and in what order listings appear (such as featured placements). This compensation does not influence our editorial content, evaluations, or rankings, which are determined independently using publicly available data. We do not review or feature every school or program available in the marketplace. Our goal is to provide accurate, unbiased information so you can make informed decisions. Read our full Advertiser Disclosure.
How to Become an AI Engineer: Degree, Steps & Salary (2026)
Key takeaway: AI engineering is an unlicensed profession -- there is no exam, board, or required certification -- but it is a demanding one, normally entered with a bachelor's degree in computer science, artificial intelligence, or a related field, strong software engineering ability, and shipped projects that use machine learning in production. The U.S. Bureau of Labor Statistics reports a national median annual wage of $135,980 for software developers, the occupational category (SOC 15-1252) that covers AI engineering roles, in its May 2025 OEWS national median.
An AI engineer is a software engineer whose systems happen to include models. The job is building and running the thing: the data pipelines that feed a model, the service that serves it, the evaluation harness that tells you whether it is getting better or worse, and the guardrails around what it is allowed to do. Research is a different job with different entry requirements.
That distinction shapes the whole path. Nobody licenses AI engineers, and no certification body controls entry, so what you need is engineering competence you can demonstrate plus enough machine learning depth to make sound decisions about models you did not train from scratch. This guide lays out the steps in order. For the broader field view, start with the Online Artificial Intelligence Degrees guide.
Step-by-step: how to become an AI engineer
Step 1: Earn a bachelor’s degree in computing or AI
Nearly every AI engineering posting asks for a bachelor’s degree, most commonly in computer science, artificial intelligence, software engineering, or a closely related technical field. A bachelor’s in artificial intelligence targets the role directly; a computer science degree with AI electives gets you to the same place.
The coursework that carries weight is data structures and algorithms, linear algebra, probability and statistics, and systems or distributed computing, alongside the machine learning sequence itself. Accredited online programs are common in computing and award the same degree as on-campus study.
Step 2: Become a competent software engineer first
This is the step that separates people who get hired from people who do not. AI engineers write production code. That means real fluency in Python, comfort with version control and code review, the ability to write tests, and enough familiarity with containers, cloud services, and CI/CD that you can put a service into production without supervision.
Candidates who arrive with model knowledge but no engineering discipline tend to stall in interviews, because the day-to-day work is far more software than mathematics.
Step 3: Build applied machine learning depth
On top of the engineering base, you need working knowledge of the modeling stack: training and fine-tuning, evaluation methodology, prompt and retrieval patterns for language models, vector search, and the practical failure modes of deployed models such as drift, data leakage, and silent degradation. A deep learning framework – PyTorch is the common choice – should be something you have used rather than read about.
The important skill is judgment: knowing when a model is the wrong tool, and how to measure whether the one you shipped is actually working.
Step 4: Ship projects that run
Because there is no credential to point at, working systems do the persuading. Two or three deployed projects outweigh a long list of tutorials. Each should have a real data source, an evaluation you can defend, and a deployed endpoint or interface someone else can use. Document the failure cases you found and what you changed. Interviewers ask about those.
Step 5: Consider a master’s – and know when it is optional
A master’s degree is not required to be an AI engineer. It matters for research-facing roles, for teams working close to the modeling frontier, and for career changers coming from a non-computing background who need the coursework and the credential together. A master’s in artificial intelligence is the direct route when that applies to you. Many practicing AI engineers hold only a bachelor’s.
Step 6: Enter through an adjacent engineering role
Very few people are hired directly into a first job titled AI engineer. The usual entry points are software engineer, backend engineer, data engineer, or ML platform engineer, followed by a move onto model-facing work once you have shipped something. That route is normal and is often faster than waiting for a title to appear. See what you can do with an artificial intelligence degree for how the adjacent roles connect.
What degree do you need to be an AI engineer?
A bachelor’s in computer science, artificial intelligence, or a related technical field is the practical baseline, and a bachelor’s in artificial intelligence is the most targeted version. No degree is legally required – self-taught engineers with strong shipped work do get hired – but the screening reality at most employers favors a computing degree, and the mathematics involved is hard to pick up incidentally.
A master’s in artificial intelligence is worth the time if you want research-adjacent work or are switching in from another field. It is not a prerequisite for engineering roles.
What AI engineers earn
The Bureau of Labor Statistics reports a national median annual wage of $135,980 for software developers (SOC 15-1252), the occupational category that covers AI engineering roles, in its May 2025 OEWS national median. For comparison from the same source, computer and information research scientists (SOC 15-1221) show a national median of $140,300, and computer systems analysts (SOC 15-1211) show $105,850.
These are medians across each full occupation. Entry-level compensation sits below the median, and pay varies widely by employer, industry, and metro area.
How long does it take to become an AI engineer?
Roughly four to seven years from a standing start.
- Bachelor’s degree: about four years full-time.
- Software engineering fundamentals and project work: six to twelve months, usually overlapping the degree.
- First engineering job before moving onto AI work: one to three years in most cases.
- Optional master’s: one to two years, if you pursue one.
There are no licensing exams or supervised-hour requirements to add to that total.
View the data behind this chart
| Percentile | Annual wage |
|---|---|
| 10th percentile | $82,460 |
| 25th percentile | $105,210 |
| Median | $135,980 |
| 75th percentile | $171,980 |
| 90th percentile | $214,670 |
View the data behind this chart
| State | Median annual wage |
|---|---|
| California | $174,410 |
| Washington | $166,540 |
| New York | $166,180 |
| Massachusetts | $165,210 |
| Oregon | $142,720 |
| New Hampshire | $139,720 |
| Maryland | $138,680 |
| Colorado | $138,390 |
Frequently asked questions
What degree do you need to be an AI engineer?
Most employers expect a bachelor’s in computer science, artificial intelligence, software engineering, or a related technical field. No specific degree is legally required, and no licensing body defines a curriculum for the role.
How long does it take to become an AI engineer?
About four to seven years, counting a four-year bachelor’s degree plus one to three years in an adjacent engineering role before moving onto model-facing work. An optional master’s adds one to two years.
How much do AI engineers make?
The Bureau of Labor Statistics reports a national median annual wage of $135,980 for software developers (SOC 15-1252), the category covering AI engineering roles, in its May 2025 OEWS national median.
Do you need a degree to be an AI engineer?
Not legally. AI engineering is unlicensed, and engineers with strong shipped systems are hired without a computing degree. In practice a bachelor’s is what most employers screen for, and the mathematics is difficult to acquire without structured coursework.
Do you need a master’s degree to be an AI engineer?
No. A master’s helps for research-adjacent roles and for career changers entering from another field, but many practicing AI engineers hold only a bachelor’s degree.
Is an AI engineer the same as a machine learning engineer?
The titles overlap heavily and many employers use them interchangeably. Where they differ, AI engineering leans toward building applications and systems around models, while machine learning engineering leans toward training, tuning, and serving the models themselves.
Next steps
- Start with the Online Artificial Intelligence Degrees guide for the full field overview.
- Compare programs on the bachelor’s in artificial intelligence and master’s in artificial intelligence pages.
- See the role map in what you can do with an artificial intelligence degree.
- Compare adjacent paths: how to become a machine learning engineer and how to become a data analyst.
Wage figures on this page come from the U.S. Bureau of Labor Statistics Occupational Employment and Wage Statistics, May 2025 national medians. Employer requirements vary; confirm expectations with the employers and programs you are considering.
Data verified: August 12, 2026. Salary, employment, and tuition figures on this page are sourced from the U.S. Bureau of Labor Statistics (OEWS May 2025; Employment Projections 2024–2034) and the U.S. Department of Education College Scorecard (2023 cohort). The source agency and data year are cited inline with every statistic.