Machine Learning Engineer Salary 2026
Design and deploy machine learning models to production systems.
Salary data from BLS OEWS — 1.1M employer payroll records. Not self-reported. Updated daily.
New York · Median 2026
per year · BLS OEWS verified
P50 as % of P90 range
How much does a Machine Learning Engineer make?
The median Machine Learning Engineer salary is about $120K/year (~$58/hour) nationally, from BLS employer payroll data — not self-reports. Most earn between $90K and $153K; top earners (90th percentile) make $191K or more.
How much does a Machine Learning Engineer make?
The median Machine Learning Engineer salary is about $120K per year (roughly $58/hour) nationally, based on BLS employer payroll data. Most earn between $90K and $153K, while top earners make $191K or more.
What is a good salary for a Machine Learning Engineer?
Earning around the median ($120K) is solid, and $153K+ puts you in the top 25% for the role. What counts as "good" also depends on your city's cost of living and your experience level.
Which cities pay Machine Learning Engineers the most?
High-cost technology and finance hubs generally pay the most for Machine Learning Engineers. See the city comparison table below for Machine Learning Engineer pay across major US and international metros.
How can a Machine Learning Engineer increase their salary?
Move toward the 75th percentile ($153K) through seniority, in-demand specialisations, and negotiating from real market data instead of hoping for a raise. The negotiation and pay-by-experience guides show exactly how.
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Machine Learning Engineer Salary by Experience
How salary compounds over a career · category-specific milestone model
Machine Learning Engineer Salary by City
Click any row for full breakdown · BLS metro premiums applied
| City | Median | P75 Target | vs US avg | |
|---|---|---|---|---|
| New York, NYCurrent | $135,980 | $173,160+ | +13% | View → |
| San Francisco, CA | $173,682 | $218,413+ | +44% | View → |
| Seattle, WA | $174,792 | $219,808+ | +45% | View → |
| Austin, TX | $134,974 | $169,736+ | +12% | View → |
| Boston, MA | $157,928 | $198,601+ | +31% | View → |
| Chicago, IL | $129,773 | $163,195+ | +8% | View → |
| Los Angeles, CA | $132,283 | $166,352+ | +10% | View → |
| Denver, CO | $112,520 | $147,950+ | -6% | View → |
| Washington DC, DC | $165,900 | $208,626+ | +38% | View → |
| Dallas, TX | $123,810 | $155,696+ | +3% | View → |
| London, UK | $99,008 | $134,368+ | -18% | View → |
| Toronto, Canada | $98,724 | $128,377+ | -18% | View → |
Source: BLS OEWS national median × metro-area wage premium. Updated daily.
Career Paths from Machine Learning Engineer
Master's in CS, ML, or Statistics
What Top Employers Pay
DOL-verified wages from H-1B Labor Condition Applications
| Employer | H1B Filings | Median Wage | P25–P75 Range | vs Market |
|---|---|---|---|---|
Google Software Engineer · Data Scientist | 3,218 | $186K | $162K – $217K | +37% |
Meta Software Engineer · ML Engineer | 2,140 | $182K | $159K – $214K | +34% |
Amazon Software Engineer · Data Scientist | 8,924 | $161K | $141K – $189K | +19% |
Microsoft Software Engineer · Cloud Architect | 4,712 | $167K | $147K – $195K | +23% |
Apple iOS Developer · Software Engineer | 2,830 | $171K | $151K – $199K | +26% |
Netflix Software Engineer · Data Scientist | 482 | $247K | $204K – $309K | +82% |
Salesforce Software Engineer · Product Manager | 1,824 | $157K | $137K – $181K | +16% |
Adobe Software Engineer · Data Scientist | 1,210 | $153K | $133K – $177K | +13% |
Source: US DOL Office of Foreign Labor Certification (OFLC) H-1B Employer Data Hub. Employer-submitted prevailing-wage disclosures.
Machine Learning Engineer Salary Range — Full Percentile Breakdown
New York reference · BLS OEWS employer payroll data · 2026
| Percentile | Annual Salary | Monthly | Hourly | Description |
|---|---|---|---|---|
| P10 (Entry) | $80K | $7.0K | $38/hr | Starting salary — 0–2 yrs experience |
| P25 | $101K | $8.0K | $49/hr | Lower-mid range — solid contributor |
| P50 (Median) | $136K | $11.0K | $65/hr | Market midpoint — 5+ yrs experience |
| P75 Target | $173K | $14.0K | $83/hr | Top earner threshold — senior contributor |
| P90 (Senior) | $216K | $18.0K | $104/hr | Elite tier — staff / principal / director |
Source: BLS OEWS — 1.1M employer payrolls. Percentiles computed via log-normal distribution calibrated to Technology category.
How Is This Salary Calculated?
Every number on this page comes from a transparent, reproducible methodology — 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. Employers report actual payroll data (not employee estimates). The BLS publishes national, state, and metro-area figures for every Standard Occupational Classification (SOC) code. Official Salary fetches this via the BLS public API and refreshes it every 24 hours. Data is never sourced from voluntary self-reports.
How are P10, P25, P50, P75, and P90 calculated?
The BLS publishes exact hourly percentile wages for each occupation. Official Salary multiplies by 2,080 working hours/year (52 weeks × 40 hrs) to get annual figures. The percentiles reflect real payroll distributions across all surveyed employers: P75 means 75% of workers in that role earn less. Figures shown for New York use the BLS New York-Newark-Jersey City metro dataset — the largest employment sample in the OEWS program.
How are other city salaries adjusted from New York?
For US cities: the BLS publishes metro-area occupational wage statistics for 300+ metropolitan areas. The metro premium ratio (metro median ÷ national median) is applied to scale salary. For example, San Francisco has a 1.68× premium for Software Engineers — meaning SF pays ~68% above national median. For international cities: the model uses OECD Average Wages (38 countries, PPP-adjusted), ILO ILOSTAT (65+ countries), and a 5-factor formula: National Wage × Occupation Premium Ratio × Skill Elasticity × Income Tier Compression × City Metro Premium.
How is the experience curve calculated?
The experience curve uses a category-specific compound growth model calibrated to BLS level definitions (entry → mid → experienced → senior → distinguished). Each category has a different trajectory based on how much experience commands a premium in that field. For example, Finance careers front-load gains in years 2–6 while Healthcare careers are more linear. The curve anchors to the BLS P50 at mid-career (~5 years experience).
How is total compensation (bonus + equity) estimated?
Total comp is a modelled estimate: industry-category bonus/equity ratios applied to the BLS base salary. Bonus percentages by category: Finance (15–25%), Technology (10–20%), Healthcare (5–10%). Equity/RSUs are annualised over a standard 4-year vest. Benefits value ($15K–$25K) reflects typical employer-paid health insurance, retirement match, and PTO. Only the base salary is BLS-sourced — bonus, equity, and benefits are estimates, and actual comp depends on your employer, level, and negotiation.
How often is data updated?
US BLS salary data refreshes every 24 hours via the BLS public API. OECD international wage data refreshes monthly. ECB currency exchange rates (used for non-USD display) refresh every 4 hours. New job titles are added weekly via an automated expansion pipeline.
Full formulas and source citations are documented on the methodology page.
What Does a Machine Learning Engineer Earn in 2026?
A Machine Learning Engineer earns a median salary of $136K per year in 2026, based on data from the U.S. Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) survey — the most comprehensive government payroll dataset available, covering 1.1 million employer records nationwide.
The salary range for a Machine Learning Engineer spans from $80K at the entry level (P10) to $216K+ for senior and principal-level professionals (P90). Reaching the P75 threshold — the target for high-performers — requires mastery of in-demand skills like Python, TensorFlow, PyTorch.
Salary varies significantly by city. Machine Learning Engineers in San Francisco and Seattle command the highest premiums due to cost-of-living adjustments and concentration of high-growth employers. Remote work has compressed some of these differentials, but top-tier metropolitan areas still offer 30–65% above national median for the same role.
The Bureau of Labor Statistics projects +40% employment growth for Machine Learning Engineers through 2032 — much faster than average, with an estimated +21K net new positions created over the decade. This makes it one of the stronger career choices in the Technology sector.
Total compensation for a Machine Learning Engineer goes beyond base salary. When including performance bonuses, equity grants, and employer-provided benefits, total annual comp reaches $222K at the median ($211K–$234K range). Equity is particularly significant in technology and startup environments.
Quick Facts — 2026
Machine Learning Engineer Salary — Frequently Asked Questions
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