TechnologyBLS OESTech Hub100/100 · Grade A+BLS.OEWS.2026.v2

Machine Learning Engineer Salary in Dallas, TX

2026 · BLS OEWS · 1.1M employer payroll records · Updated daily

Median salary
$176,048
per year
P75 target
$221,388
negotiation anchor
Hourly rate
$85/hr
2,080 hr/yr baseline
+4%
vs US avg
+45%
demand growth
Low
AI risk

Salary Distribution — Dallas

P10Entry Level
$113,849

New graduates, 0–1 yr exp

P2525th Percentile
$139,994

1–3 years experience

P50Median
$176,048

3–7 years, typical professional

P7575th Percentile
$221,388

Senior / high-performer — target

P90Top 10%
$272,227

Staff / principal / lead

Data Confidence
100/100A+
Government earnings data30/30

Bureau of Labor Statistics — OEWS federal authority

BLS Spring 2026 release40/40

1mo since last update

Multi-city cross-validation16/16

8 cities validated

Full percentile coverage14/14

P10, P25, P50, P75, P90 + hourly rate

BLS.OEWS.2026.v2Updated Jun 12, 2026

Machine Learning Engineer Salary by Experience Level in Dallas

How compensation grows from entry-level through staff / lead

Experience LevelYearsPercentileAnnual SalaryMonthlyHourly
Entry00 yrs$119,713$9,976$58
Junior22 yrs$147,880$12,323$71
Mid-LevelTypical44 yrs$166,659$13,888$80
Senior66 yrs$192,949$16,079$93
Staff1010 yrs$260,551$21,713$125
Principal1414 yrs$326,745$27,229$157
Distinguished1818 yrs$343,294$28,608$165

Based on BLS OEWS percentile distribution. Actual salary depends on employer, skills, and negotiation.

Skills That Earn More — Machine Learning Engineer

Estimated premium above the Dallas median based on market demand

Python+6% ≈ +$11K/yr
TensorFlow+10% ≈ +$18K/yr
PyTorch+11% ≈ +$19K/yr
MLOps+12% ≈ +$21K/yr
Kubernetes+9% ≈ +$16K/yr

Estimates based on job-posting salary premiums for verified high-demand skills.

Top Skills Market Premium

Real premium data from LinkedIn, StackOverflow & Levels.fyi job postings

All-skills combined premium
+$85K/yr
Highest single skill
Python +6%
Python+6% · +$11K/yr
TensorFlow+10% · +$18K/yr
PyTorch+11% · +$19K/yr
MLOps+12% · +$21K/yr
Kubernetes+9% · +$16K/yr

Premiums represent verified market uplift for each skill based on job posting analysis. Adding the top-3 skills compounds — but employers rarely pay all premiums simultaneously.

Machine Learning Engineer Intelligence Report

Composite career metrics and full compensation breakdown — computed from BLS demand data

Career Opportunity Score

Composite: demand growth × 1.4 + (100 − AI risk) × 0.4

A+94/100
High RiskModerateExceptional
Demand Growth+45%/yr
AI Displacement Risk22% — Low
Risk-Adj. Salary Growth+5.9%/yr
Exceptional: Explosive demand + low AI displacement — top career momentum of any field.
BLS Official 10-yr OutlookMuch faster than average
+40%
Growth 2022–2032
+21K
New jobs projected
$197K
In 2 yrs
$234K
In 5 yrs
$312K
In 10 yrs

BLS OOH employment outlook · Risk-adjusted growth model. Not financial advice.

Total Compensation — Machine Learning Engineer

Beyond base salary: bonus, equity, and employer-provided benefits

Total Comp Range
$273K$303K
per year
Base (61%)Bonus (10%)Equity (15%)Benefits (13%)
Base Salary
Median market rate
$176,048
Annual Bonus
Typical range: 8–25% of base
$29,048
Equity (annualised)
~25% of base — RSUs/options
$44,012
Benefits Value
~22% — healthcare, 401k, PTO
$38,731
Total Comp (mid)
$287,839

Sources: Levels.fyi TC data, LinkedIn Salary Insights, Robert Half 2025 Guide. Equity assumes established company RSU vesting schedule.

Typical Benefits for Machine Learning Engineers

Total compensation beyond base salary — often adds 20–35% to your effective pay

Health Insurance
Medical, dental, vision
401(k) Match
Avg 3–6% employer match
PTO
15–25 days / year
Remote / Hybrid
Common in this role
Equity / RSUs
Especially at tech firms
Learning Budget
$1,000–$3,000 / year
Total compensation tip: Always negotiate base salary first. Equity, signing bonus, and remote flexibility have the highest negotiation leverage in the current market.

Compare Machine Learning Engineer Salaries by City

How Dallas, TX stacks up against other major markets

CityMedianP75vs US avg
Dallas, TX (current)$176,048$221,388++4%
New York, NY$250,510$315,027++48%
San Francisco, CA$281,690$354,237++67%
Seattle, WA$245,169$308,311++45%
Austin, TX$190,362$239,388++13%
Boston, MA$237,946$299,227++41%
Chicago, IL$195,637$246,022++16%
Los Angeles, CA$234,282$294,620++39%
Denver, CO$187,822$236,194++11%

Career Paths from Machine Learning Engineer

O*NET · US Dept of Labor

Master's in CS, ML, or Statistics · Skill overlap and transition difficulty from O*NET

Key tasks for this role
Deploy ML models to productionBuild feature pipelinesMonitor model performanceOptimise inference latency

Frequently Asked Questions

What is the average Machine Learning Engineer salary in Dallas, TX?

The median Machine Learning Engineer salary in Dallas, TX is $176K per year (2026), based on BLS OEWS employer payroll data from 1.1 million employers. The top 25% earn $221K+ per year.

What is a good Machine Learning Engineer salary in Dallas, TX?

The 75th percentile ($221K/yr) is the professional benchmark — what the top quarter already earns. It's a documented, negotiable target backed by BLS payroll data. Anything above the median ($176K) is above-average for this role in Dallas, TX.

How much does a Machine Learning Engineer earn per hour in Dallas, TX?

Based on the median annual salary of $176K, a Machine Learning Engineer in Dallas, TX earns approximately $85/hr (2,080-hour work year). The P75 rate is ~$106/hr.

Is Dallas, TX a good market for Machine Learning Engineers?

Dallas, TX pays 4% above the US national average for this role. Demand for Machine Learning Engineers is growing 45% annually, and AI automation risk is rated low for this occupation.

How do I negotiate a higher Machine Learning Engineer salary in Dallas, TX?

Cite the BLS P75 figure ($221K) — it is verifiable public data from government payroll records. Request the full compensation package: base + equity/bonus + benefits. Timing matters: negotiate at the offer stage, not after acceptance. Counter with a specific number, not a range.

How Is This Salary Calculated?

Every number on this page is derived from a transparent, reproducible methodology — no estimates, no black boxes.

Where does the salary data come from?

All US figures come from the BLS Occupational Employment and Wage Statistics (OEWS) survey — a mandatory biannual survey of 1.1 million US employers who report actual payroll data. The BLS publishes national, state, and metro-area percentile wages for every Standard Occupational Classification (SOC) code. SalaryScope fetches this via the BLS public API and refreshes every 24 hours. No self-reported data is used at any stage.

How is the Dallas figure calculated?

The BLS publishes metro-area occupational wage statistics for 300+ US metropolitan areas. For Dallas, SalaryScope uses the BLS metro premium ratio (metro median ÷ national median) and applies it to the national baseline. This ratio accounts for local employer density, cost-of-living, and industry concentration. The figures are updated whenever the BLS releases new OEWS metro data.

What do P10, P25, P50, P75, and P90 mean?

These are salary percentiles from employer payroll records. P50 (median) means 50% of workers earn less — this is the market midpoint. P75 means 75% of workers earn less — this is the "top 25% earners" threshold and is the recommended negotiation anchor. P10 and P90 represent the bottom 10% and top 10% of earners respectively. All figures are annual and based on 2,080 working hours per year (52 × 40hrs).

How is total compensation (bonus + equity) estimated?

Total comp is estimated using industry-specific compensation models calibrated to publicly available surveys (LinkedIn Salary, Radford, Levels.fyi). Bonus percentages are set by category: Finance (15–25%), Technology (10–20%), Healthcare (5–10%). Equity/RSUs are annualised over a standard 4-year cliff vest. Benefits value ($15K–$25K) reflects average employer-paid health, retirement match, and PTO. These are estimates — your actual comp depends on employer, level, and negotiation.

How often is data updated?

US BLS salary data refreshes every 24 hours via the BLS public API. OECD international wages refresh monthly. ECB currency rates refresh every 4 hours. The timestamp shown on each page reflects the most recent BLS data pull for that occupation.

Full formulas and source citations on the methodology page.

How much of $176,048 do you actually take home?

Calculate exact net pay after federal, state, and FICA taxes — 2026 brackets.

Machine Learning Engineer Salary Trend (2019–2024)

BLS OES historical national medians — 6-year progression

6-yr CAGR
+8.9%/yr
2019
$112K
2020
$119K
+6%
2021
$131K
+10%
2022
$146K
+12%
2023
$160K
+10%
2024
$172K
+7%
2019 median
$112K
2024 median
$172K

Source: BLS Occupational Employment & Wage Statistics (OEWS) 2019–2024. City-level data uses national trend × metro premium.

Inflation note: In 2019 dollars, today's median is ~$149K — 18% of nominal salary is inflation (2019–2024 CPI avg 3.4%/yr).

Education Premium — Machine Learning Engineer

How degree level affects Machine Learning Engineer salary · ACS Census data

High School / GED
-28%
~$127K
Associate's Degree
-12%
~$155K
Bachelor's DegreeBASELINE
~$176K
Master's Degree
+24%
~$218K
Doctoral (PhD)
+32%
~$232K
Professional (MBA/JD/MD)
+42%
~$250K

Source: US Census Bureau ACS PUMS Table B20004 · BLS OES wage data. Premiums shown vs bachelor's degree baseline at median experience.

Am I Paid Fairly?

Enter your current salary to instantly see where you rank in the Dallas market and get your data-backed negotiation opening ask.

📊Your exact market percentile based on BLS distribution
🎯P75 target + 10% stretch as your opening ask price
🚪Walking-away floor so you know when to move on
Dallas benchmarks
$176K
Market median
$221K
P75 target
$272K
Top 10%

Negotiation Calculator

Enter your current salary to see your market position and opening ask

$
Machine Learning Engineer in Dallas — Distribution
P10
$114K
P25
$140K
P50
$176K
P75
$221K
P90
$272K
Enter your salary above to see your negotiation position

Data Source & Attribution

Salary data sourced from the U.S. Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) survey, based on 1.1 million employer payroll records. Data is updated via ISR (Incremental Static Regeneration) and reflects the most recent BLS OEWS release cycle. This data is in the public domain under BLS data dissemination policy.

BLS.OEWS.2026.v2

Jun 12, 2026

Full methodology →