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machine learning Salary in california

Based on 2814 active job postings in california  ·  Updated 2026

Min Salary
$195,000
per year
Average Salary
$374,420
per year
Max Salary
$583,000
per year
Jobs Found
2814
active listings

✨ AI Compensation Insight SALARY INSIGHTS

Generating real-time market insights and estimated salary range for machine learning in california...

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Open machine learning Jobs in california 2814

Head of Machine Learning
Earnin Mountain View, California
$583000 / per year Full Time
Machine Learning Infrastructure Engineer, Safeguards Research
Anthropic San Francisco, California
$500000 / per year Full Time
Remote Staff Machine Learning Scientist (Remote)
grabjobs Fremont, California Remote
$302400 / per year Full Time
Remote Senior Machine Learning Engineer, Model Risk Management
grabjobs San Francisco, California Remote
$291700 / per year Full Time
Remote Senior Machine Learning Engineer
grabjobs San Diego, California Remote
$195000 / per year Full Time
Machine Learning Engineer Azure Aiml Retail
Stage Solutions Inc San Francisco, California
$114400 / per year Full Time
Senior Machine Learning Engineer
Unity Mountain View, California
Full Time
Remote Machine Learning Expert
grabjobs San Francisco, California Remote
Full Time
Machine Learning Engineer - Credit
Plaid San Francisco, California
Full Time
Remote Senior Machine Learning Engineer, Computer Vision
grabjobs Irvine, California Remote
Full Time
1 2 3 4 5 6 7 8 9 10 Next →

machine learning Salary FAQ

What is the average machine learning salary in california?
Based on 5 recent job postings, the average annual salary for a machine learning in california is approximately $374,420, with a range of $195,000 – $583,000.
How do I negotiate my machine learning salary?
Research comparable roles in your area, document your accomplishments, and arrive at negotiations with data. Use total compensation (base + bonus + equity + benefits) as your benchmark, not just base pay.
What factors affect machine learning compensation in california?
Key factors include years of experience, technical certifications, company size (startup vs. enterprise), industry (tech vs. finance vs. healthcare), and whether the role is remote-first or on-site in a high cost-of-living metro.