National median base salary of $128,000, with a typical range of $82,000 to $230,000 depending on level, metro and industry.
Python developers in the United States typically earn a base salary between $82,000 and $230,000, with a national median near $128,000. Entry-level Python developers commonly start between $82,000 and $108,000; mid-level developers earn about $127,000; senior developers cluster near $162,000; and leads or Python-heavy machine-learning engineers reach $195,000 and above. Data and ML-adjacent Python roles pay roughly 10–20% above general web backend work.
Base salary bands by seniority. Ranges are national; see the metro table below for location adjustments.
| Level | Experience | Range | Median |
|---|---|---|---|
| Junior Python Developer | 0–2 years | $82K – $108K | $94,000 |
| Mid-level Python Developer | 2–5 years | $108K – $148K | $127,000 |
| Senior Python Developer | 5–8 years | $140K – $190K | $162,000 |
| Lead / Principal | 8+ years | $170K – $230K | $195,000 |
Indicative US base-salary ranges for 2026, compiled from publicly posted pay ranges and published industry salary surveys. Figures are base salary only — they exclude bonus, equity and benefits — and actual pay varies by employer, metro, industry and individual experience.
Cost of labour is the largest single source of pay variance. These figures apply each metro's adjustment to the $128,000 national median.
| Metro | vs national | Adjusted median |
|---|---|---|
| San Francisco Bay Area, CA | +28% | $164,000 |
| Seattle, WA | +20% | $153,500 |
| New York, NY | +18% | $151,000 |
| Boston, MA | +12% | $143,500 |
| Los Angeles, CA | +10% | $141,000 |
| Washington, DC | +8% | $138,000 |
| Austin, TX | +6% | $135,500 |
| Chicago, IL | +4% | $133,000 |
| Denver, CO | +2% | $130,500 |
| Dallas–Fort Worth, TX | +1% | $129,500 |
| Atlanta, GA | -3% | $124,000 |
| Phoenix, AZ | -5% | $121,500 |
Python has the widest role coverage of any mainstream language — web, data, automation, scientific computing and machine learning. Pay growth is concentrated in data-platform and ML engineering, while general Django and Flask web work tracks the broader backend market.
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