Machine Learning Engineering salaries in California
Machine Learning Engineering professionals in California earn $157.3–253K per year on average, based on 12 jobs. Machine Learning Engineering roles in California pay 11% above the board-wide average of $149.8–220.7K for Machine Learning Engineering jobs on LumiJobs. Pay ranges from $182.2–228.3K for Mid-level roles up to $148.9–256.4K at the Senior level.
Average salary range
$157.3–253K
Based on 12 jobs · 11% more than the average salary on LumiJobs
25th percentile
$117.5K
Average
$205.1K
75th percentile
$299.5K
Machine Learning Engineering salaries by seniority in California
Machine Learning Engineering salaries in California range from $182.2–228.3K for Mid-level roles to $148.9–256.4K for Senior positions.
| Seniority | Avg. salary | Jobs | vs Avg. on LumiJobs |
|---|---|---|---|
| Mid-level | $182.2–228.3K | 3 | +11% |
| Senior | $148.9–256.4K | 8 | +9% |
Other top paying titles in California
Highest paying job titles in California beyond Machine Learning Engineering, ranked by average salary.
Software Engineering
Avg. $163.3–235.6K · 57 jobs
Backend Engineering
Avg. $165.1–245.1K · 30 jobs
Machine Learning Engineer
Avg. $177.8–278.3K · 18 jobs
Software Engineer
Avg. $149.4–238.4K · 17 jobs
AI Engineer
Avg. $166.9–246.6K · 12 jobs
Backend Development
Avg. $158.2–237.3K · 12 jobs
Top paying skills in California
Highest paying skills in California, ranked by average salary.
Python
Avg. $158.4–230.3K · 83 jobs
C++
Avg. $152.9–215.4K · 32 jobs
CI/CD
Avg. $149.6–219.5K · 32 jobs
AWS
Avg. $166–236.9K · 31 jobs
TypeScript
Avg. $163.3–233.1K · 30 jobs
Machine Learning
Avg. $171.3–258.4K · 29 jobs
Other locations for Machine Learning Engineering
Compare Machine Learning Engineering salaries in other locations.
United States
Avg. $146.5–221.5K · 43 jobs
New York
Avg. $181.5–235.3K · 10 jobs
San Francisco, CA
Avg. $160.3–263.3K · 5 jobs
Seattle, WA
Avg. $172.3–233.9K · 3 jobs
Texas
Avg. $122–172.1K · 3 jobs
Machine Learning Engineering salary FAQs for California
All salary figures are normalized to USD annual equivalents. Averages are based on published jobs with salary data and filtered for statistical outliers.