Artificial Intelligence Engineer Salary Guide

Current sources answer different pay questions, so a useful comparison must separate average base salary, median estimated total pay, and median total compensation.

Benchmark the sources separately: Indeed reports $153,277 in average US AI/ML engineer base salary, Glassdoor reports about $144,000 in median estimated total pay for US AI engineers, and Levels.fyi reports $155,000 in median total compensation for US AI engineers.

AI Engineer Salary in the United States

Three current salary sources provide different views of US AI engineer pay. Their numbers should remain separate because an average is not a median, and base salary is not total compensation.

Source and date	Population and metric	Central estimate	Reported range or percentiles
Indeed, August 3, 2026	US AI/ML engineer average base salary	$153,277	$90,404 low to $259,876 high
Glassdoor, displayed update April 10, 2025; retrieved August 24, 2026	US AI engineer median total pay	About $144,000	$115,000 to $182,000 likely total-pay range
Levels.fyi, August 24, 2026	US AI engineer median total compensation	$155,000	$110,000 at the 25th percentile, $218,000 at the 75th, $300,000 at the 90th

On retrieval, Glassdoor simultaneously displayed the April 10, 2025 update date and 982 submitted salaries. Treat the date as the page’s update label, not as the date of that submission count.

These terms define what each number includes:

• Base salary is fixed annual cash pay before bonuses, stock, and benefits.
• Additional cash compensation includes cash paid above base, such as a target performance bonus or signing bonus. A target bonus depends on plan terms and performance. A signing bonus is usually limited to a stated period. Glassdoor’s broader “additional pay” category is not a cash-only measure and may include cash bonus, stock, commission, profit sharing, or tips.
• Total compensation combines base salary with other pay components. Levels.fyi defines yearly total compensation as base salary plus yearly stock compensation plus bonus. For new offers, it uses base salary, average annualized initial stock, and annualized bonuses, spreading a signing bonus over a typical four-year vesting period and adding the target bonus. For existing employees, it uses current base salary, annual stock compensation, and ongoing bonus.
• Percentiles show position within a reported distribution. A 75th-percentile figure means 75 percent of reported values are at or below it. It does not guarantee that a candidate with a certain number of years of experience will receive that amount.
• Range describes the lower and upper values or estimates supplied by the source. It is not a promise that every employer hires across the full span.

Glassdoor also reports a likely base-pay range of $90,000 to $135,000 and an additional-pay range of $25,000 to $47,000. Its additional-pay category may include cash bonus, stock, commission, profit sharing, or tips, so the range cannot be treated as cash-only bonus compensation. That can coexist with its higher total-pay figures because additional pay may add to base.

The existing AI engineer salary guide provides related career context. The comparison here focuses more narrowly on reconciling pay metrics and evaluating an actual offer.

Why AI Engineer Salary Estimates Disagree

An apples-to-apples salary benchmark uses the same role family, geography, seniority, pay metric, and time period. Change any one of those inputs and the result may answer a different question.

The current sources differ in several ways:

Source	What the reported figure measures	Data basis	Main comparison risk
Indeed	Average base salary for US AI/ML engineers	1,700 salaries taken from job postings during the preceding 36 months	Excludes bonus and stock, and combines AI and ML wording
Glassdoor	Median estimated total pay for US AI engineers	Proprietary machine-learning model using user-submitted salaries and government data; 982 salaries displayed on retrieval	Modelled total pay cannot be compared directly with base-only data
Levels.fyi	Median total compensation for US AI engineers	Crowdsourced reports entered manually or supported by proof documents such as offer letters, W-2s, or pay statements; submissions are reviewed, cleaned, and normalized	Annualization rules and the platform’s represented employers and workers can affect the result
BLS	Wages for defined occupations	Occupational wage estimates based on job duties	BLS has no single universal AI engineer occupation

Indeed’s $153,277 figure is an average, so higher values can pull it upward. The Glassdoor and Levels.fyi central figures are medians, which identify the middle reported value. That difference alone prevents a clean ranking of the three figures.

The pay definitions differ too. Indeed reports base salary. Glassdoor reports estimated total pay and a separate base-pay range. Levels.fyi includes base, yearly stock compensation, and bonus in total yearly compensation.

BLS data needs a separate interpretation. Its Occupational Employment and Wage Statistics estimates cover wages and salaries. They exclude nonproduction bonuses, stock bonuses, overtime, and employer benefit costs such as health insurance and retirement contributions. A BLS wage median therefore cannot stand in for a stock-heavy technology offer.

There is also no official BLS median for all people whose employer calls them an AI engineer. BLS warns that workers with the same job title can fall into different occupations according to their individual duties. A person building AI features into an application may align more closely with software development. Someone running statistical analyses may align with data science. A researcher creating new computational methods may align with computer and information research science.

A dated benchmark should therefore be written as a complete statement: source, date, geography, role, statistic, and pay metric. “Indeed reported average US AI/ML engineer base salary of $153,277 on August 3, 2026” is comparable. “AI engineers earn $153,277” discards the qualifications that make the number useful.

How Pay Varies by Location and Why Level and Employer Still Matter

Entry, mid-level, senior, and staff are employer-specific levels, not universal salary bands. One employer’s senior engineer may own a service independently. Another may expect that same scope at mid-level. Titles become more useful when paired with the work, reporting structure, and compensation level.

A practical scope comparison looks like this:

Level label	Scope to examine in the job description
Entry	Completes bounded work with review and established technical direction
Mid-level	Owns production tasks or a defined system area with increasing independence
Senior	Leads difficult projects, resolves ambiguity, and influences work beyond personal assignments
Staff	Sets direction across teams or systems and handles broad technical tradeoffs

These descriptions are guides for comparing responsibility. They do not create fixed salary ranges. The software engineer career ladder explains why scope and influence matter more than the title printed beside a role.

Location also changes the observed benchmark. Indeed’s August 3, 2026 average AI/ML engineer base-pay estimates were:

City	Average base pay
Seattle	$229,274
San Francisco	$213,830
Santa Clara	$193,021
New York City	$187,699

These are city-level Indeed estimates, not guaranteed offers and not total-compensation figures. They should be compared with the same source’s national base-pay estimate rather than with Levels.fyi total compensation. The figures also do not provide a cost-of-living adjustment or an estimate of take-home pay.

Employer type changes the compensation mix. A company may put most of the offer into predictable cash. Another may combine base pay with a large equity grant. The second package can have higher stated total compensation while exposing the employee to more price, vesting, and liquidity uncertainty.

At employers that use equity-heavy packages, examine:

• The number or value of shares scheduled to vest each year
• Whether the vesting schedule is even or concentrated in particular years
• The valuation used to express the grant in dollars
• Whether the company is public or private
• What happens to unvested stock after departure
• Whether refresh grants are expected, discretionary, or already documented
• Whether a signing bonus must be repaid after an early departure

Staff roles deserve extra care because their scope varies sharply. The guide to what a staff engineer does gives a better comparison basis than title alone. A staff candidate should price the organizational responsibility, technical risk, and decision authority in the role, then examine whether the cash and equity mix compensates for that scope.

Which AI Role Are You Actually Pricing?

“AI engineer” can describe several kinds of work. Use the job’s recurring duties to choose a role family before selecting a salary benchmark.

Role family	Typical duties	Most relevant benchmark
Product AI engineer	Integrates models into applications, builds services around them, evaluates outputs, and operates production features	The available current sources do not isolate this role; use generic AI engineer data and a software developer proxy, clearly labelled, when application engineering dominates
Machine-learning engineer	Builds training or inference pipelines, prepares production data flows, deploys models, and monitors system behavior	The available current sources do not support a separate like-for-like figure; use dated AI/ML or machine-learning data only when geography, level, population, and pay metric are stated
Data scientist	Analyzes data, designs experiments or models, communicates findings, and supports decisions with statistical work	Data scientist occupational or role-specific data
Computer research scientist	Investigates new computational methods and conducts research-oriented technical work	Computer and information research scientist wage data

These families overlap, but they are not interchangeable. A product AI engineer and a computer research scientist can both work with models while having different daily work, hiring criteria, and compensation structures.

For broad occupational context, the latest BLS OEWS release reported these May 2025 median annual wages:

• Software developers: $136,000
• Data scientists: $120,220
• Computer and information research scientists: $140,300

Those are wage figures for BLS occupations, not AI engineer total-compensation estimates. Select the nearest proxy by duties and state the limitation. Do not choose the research-scientist figure merely because it is the highest of the three.

Job descriptions provide better evidence than titles. Look for the work that occupies most of the role:

• Application APIs, user features, deployment, and production ownership point toward product AI engineering.
• Training systems, model serving, feature or data pipelines, and monitoring point toward machine-learning engineering.
• Statistical analysis, experiments, forecasts, and decision support point toward data science.
• Novel methods, research agendas, and experimental publications point toward computer research science.

This classification also improves interview preparation. A product engineering role may test software design and production reliability alongside model evaluation. A research role may place more weight on research depth. The coding interview preparation roadmap can structure the general programming portion after the role family is clear.

How to Compare an AI Engineer Offer

Compare offers with a worksheet that separates guaranteed cash, target cash, and equity. Do not begin with the headline total.

Use one exact comparison window. Here, “first year” means the first 12 months after the start date. Include only base earned, bonuses for which the employee is eligible, and stock scheduled to vest inside that window; record any bonus proration, vest dates, and cliffs.

Use these calculations:

1. Guaranteed first-year cash equals base salary earned within the window plus any guaranteed signing bonus paid within it.
2. Target first-year cash equals base salary earned within the window plus the target bonus attributable to it after any proration, plus any signing bonus paid within it.
3. Annual vested stock equals the portion of the grant scheduled to vest within the window after applying vest dates and cliffs, valued under one stated method.
4. Target first-year direct compensation equals target first-year cash plus first-year vested stock.
5. Recurring target compensation removes one-time signing pay and uses the stock scheduled for the recurring comparison year.
6. Refresh grants remain separate unless a grant has been awarded and its vesting terms are known.

Consider two hypothetical US offers:

Component	Offer A	Offer B
Start date	September 1, 2026	September 1, 2026
First-year comparison window	September 1, 2026 to August 31, 2027	September 1, 2026 to August 31, 2027
Bonus eligibility and proration	Eligible for the full target bonus; no proration	Eligible for the full target bonus; no proration
First vest and cliff assumption	$60,000 vests within the window; no cliff moves it outside	$18,000 vests within the window; no cliff moves it outside
Base salary	$180,000	$205,000
Target bonus	10%, or $18,000	10%, or $20,500
Signing bonus	$25,000	$0
Headline equity grant	$240,000	$180,000
Vesting schedule	$60,000 each year for four years	$18,000, $36,000, $54,000, then $72,000
Expected refresh grant	Mentioned but not guaranteed	None stated

The first-year worksheet is:

Calculation	Offer A	Offer B
Guaranteed first-year cash	$205,000	$205,000
Target first-year cash	$223,000	$225,500
First-year vested stock	$60,000	$18,000
Target first-year direct compensation	$283,000	$243,500
Year-two recurring target compensation, including year-two stock	$258,000	$261,500

Offer A has the higher first-year target because of its signing bonus and larger first-year vest. Offer B has the higher base salary and target cash. Its stock schedule grows later, so comparing only the full $180,000 grant with Offer A’s full $240,000 grant would hide the timing.

For year two, remove Offer A’s signing bonus and use the second-year vest:

• Offer A: $180,000 base + $18,000 target bonus + $60,000 stock = $258,000.
• Offer B: $205,000 base + $20,500 target bonus + $36,000 stock = $261,500.

These totals assume the target bonus is paid and the assigned stock values hold under the chosen valuation method. Keep a second row for guaranteed cash because a target bonus is not the same as guaranteed pay.

For public-company stock, record the share count, vest date, and price assumption. The eventual value changes with the share price. For private-company equity, the stated paper value may not be cashable when it vests. Compare at least two scenarios: one that excludes private equity and one that includes the employer’s stated value. This makes the uncertainty visible instead of burying it inside one precise total.

Refresh grants need similar discipline. A recruiter’s statement that refreshers are common is not an awarded grant. Record it as a possible future component, not current compensation.

The anonymous Reddit package illustrates why the breakdown matters. The post reported $532,970 in forward annual direct compensation: $230,000 base, $23,000 target bonus, and $279,970 in annual restricted stock units. Stock represents more than half of that stated package. It is one exceptional, anonymous self-report, not a typical AI engineer salary or a substitute for the broader benchmarks.

How to Improve Your Salary Position

A stronger salary case connects requested compensation to demonstrated scope. Show evidence that matches the role family and level being priced.

Useful evidence includes:

• Ownership of a production AI feature from design through operation
• Model evaluation tied to explicit quality and failure criteria
• Data pipelines that remain observable and recoverable when inputs fail
• Reliability work such as monitoring, incident response, and safe deployment
• Cost control supported by measurements and documented tradeoffs
• Technical leadership across projects, systems, or teams
• Clear design records that explain rejected options and operational consequences

A portfolio or interview story should name the problem, constraints, personal decisions, measurable result, and what changed after deployment. Avoid presenting a list of tools as proof of seniority. Employers price responsibility and credible execution differently from surface familiarity.

Credentials may help a candidate pass a screen, but the supplied salary data does not establish that a particular degree, certification, language, or AI skill causes a stated pay increase. Use credentials to support the job’s requirements, not as a salary formula.

The employment outlook is positive for one relevant family: BLS projects data scientist employment growth of 34 percent from 2024 through 2034. That projection applies to the data scientist occupation, not every job carrying an AI engineer title. Software development and computer research science remain useful wage proxies when their defined duties better match the role.

For advanced engineering roles, Java for Staff Engineers helps with the architecture, runtime, concurrency, and technical judgment expected when an AI system sits inside a larger production platform. Pair that depth with a written offer worksheet, role-specific benchmarks, and evidence of owned scope so the final negotiation rests on comparable numbers rather than a headline salary.