What is the median Machine Learning Engineer salary in San Francisco?

On Ganloss, the observed median is about $185,000/year for Machine Learning Engineer roles in San Francisco, with a range of $75,000–$235,000 (8 listings with pay shown).

How do I negotiate pay as a Machine Learning Engineer?

Use Ganloss listings and role guides as comparables, quantify production impact, and run our salary negotiation simulator before you counter an offer.

Are these salary numbers reliable?

They come from Ganloss job posts with visible compensation. They reflect the current US hiring market on the platform, not a national survey.

Is Machine Learning Engineer pay higher in San Francisco than San Francisco?

SF and NYC often show 10–20% higher medians, but cost of living and remote/hybrid options rebalance the math. Compare city salary guides on Ganloss.

Freelance vs full-time: how do rates compare?

As a contractor, target a day rate that covers taxes, gaps between gigs, and time off (often 1.3–1.5× the equivalent W-2 daily rate). Ranges here focus on salaried roles with listed pay.

Salary guide

Machine Learning Engineer salary in San Francisco (2026)

3 min readUpdated November 2026

How much does a machine learning engineer make in San Francisco? Median $185,000, range $75,000–$235,000. Based on 8 Ganloss listings · California.

What does a machine learning engineer earn in San Francisco in 2026? This guide uses 8 Ganloss listings with visible pay in California. Median: $185,000/year — observed range $75,000–$235,000.

Ranges observed on Ganloss

Among open listings with visible pay in San Francisco, the median total compensation for Machine Learning Engineer roles is about $185,000/year. Observed spread: $75,000–$235,000, depending on experience, contract type (full-time, contract), and seniority.

Machine Learning Engineer market in San Francisco

San Francisco is an active AI hiring market in California. Recruiters post full-time, contract, and sometimes freelance roles on Ganloss. Compare this guide with live listings to refine your range by seniority and company type (startup, agency, enterprise).

Pay trends and 2026 outlook

GenAI, production LLM, and MLOps profiles still command a premium. Mid to senior moves often add 15–25% on median pay. Hybrid or full remote can offset a lower base versus high-cost hubs like San Francisco or NYC.

What moves the number

Stack (LLM, MLOps, cloud), remote vs on-site, company stage (startup vs enterprise), and profile scarcity. Production GenAI and LLM roles still command a premium in 2026. Local demand in San Francisco (San Francisco and the Bay Area host the largest share of US AI hiring: LLM, MLOp…) also matters.

Negotiate the full package

Bring comparables (Ganloss listings, role guides), highlight shipped production work, and discuss equity, bonus, PTO, and learning budget—not just base pay. Use our salary negotiation tool before the final conversation.

Go further

FAQ

What is the median Machine Learning Engineer salary in San Francisco?: On Ganloss, the observed median is about $185,000/year for Machine Learning Engineer roles in San Francisco, with a range of $75,000–$235,000 (8 listings with pay shown).
How do I negotiate pay as a Machine Learning Engineer?: Use Ganloss listings and role guides as comparables, quantify production impact, and run our salary negotiation simulator before you counter an offer.
Are these salary numbers reliable?: They come from Ganloss job posts with visible compensation. They reflect the current US hiring market on the platform, not a national survey.
Is Machine Learning Engineer pay higher in San Francisco than San Francisco?: SF and NYC often show 10–20% higher medians, but cost of living and remote/hybrid options rebalance the math. Compare city salary guides on Ganloss.
Freelance vs full-time: how do rates compare?: As a contractor, target a day rate that covers taxes, gaps between gigs, and time off (often 1.3–1.5× the equivalent W-2 daily rate). Ranges here focus on salaried roles with listed pay.

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