Jobiba Salary Intelligence
Machine Learning Engineer salary in Foster City
Salary range, market position, recent movement, location comparisons and matching live jobs—calculated from comparable Jobiba listings rather than copied salary tables.
Typical market range
$265,000–$302,000
Median $295,000 / year
Based on 5 salary-listed job postings from the last 12 months · refreshed 22 Oct 2026
How these figures are built →Analyze my salary →Salary distribution
Where the market sits
$265,000
25th percentile
$295,000
Market median
$302,000
75th percentile
$247,600
Lower market
$265,000
25th percentile
$302,000
75th percentile
$306,800
Upper market
Market movement
Not enough historical evidence yet. Trend is shown only when both 90-day windows have enough comparable observations, preventing noisy “growth” claims from tiny samples.
Location intelligence
Compare Machine Learning Engineer pay by market
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Live opportunity layer
Machine Learning Engineer jobs in Foster City
Senior / Staff Machine Learning Engineer - Behavior Models for Road Users
Foster City, California, United States
$254K – $366K/yr
Listed salary · employer/source provided
Senior / Staff Machine Learning Engineer - 3D Sensor Simulation
Foster City, California, United States
$242K – $348K/yr
Listed salary · employer/source provided
Senior Machine Learning Engineer - Perception
Foster City, California, United States
$225K – $305K/yr
Listed salary · employer/source provided
Senior Machine Learning Engineer - Perception 3D Segmentation
Foster City, California, United States
$254K – $350K/yr
Listed salary · employer/source provided
Senior Staff / Principal Machine Learning Engineer - Autonomy Behaviors
Foster City, California, United States
$340K – $492K/yr
Listed salary · employer/source provided
Machine Learning Engineer - 3D Sensor Simulation
Foster City, California, United States
$189K – $283K/yr
Listed salary · employer/source provided
How Jobiba calculates this
Evidence first, estimate second
- • Uses recent active Jobiba listings that contain employer/source salary data.
- • Requires an explicit salary currency and pay period before a listing can enter an aggregate.
- • Applies broad currency-specific plausibility floors/ceilings, then rejects extreme statistical outliers.
- • Groups title variants through Jobiba's canonical salary-role taxonomy so current estimates and historical trends use the same comparable cohort.
- • Annualizes hourly, daily, weekly and monthly pay; no foreign-exchange conversion is used.
- • Uses percentile medians and publishes a range only after the minimum comparable sample is reached.
- • Labels inferred pay on salary pages/jobs as a Jobiba estimate, never as employer-provided compensation.
Based on 5 salary-listed job postings from the last 12 months · refreshed 22 Oct 2026
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