Jobiba Salary Intelligence
Senior Software Engineer Machine Learning salary in Mountain View
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
Pay data under review
These figures did not pass Jobiba's consistency checks, so we are not showing them until the data is reviewed. Live jobs below are still current.
Analyze my salary →Salary distribution
Where the market sits
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 Senior Software Engineer Machine Learning pay by market
Currencies are never blended or silently converted
San Mateo
57 samples$242,100
$220,020–$269,270 typical
San Francisco
41 samples$216,000
$195,000–$240,000 typical
Toronto
25 samplesCA$161,500
CA$137,000–CA$165,000 typical
New York
21 samples$216,000
$215,000–$226,800 typical
Mountain View
9 samples$193,930
$160,360–$193,930 typical
Bellevue
8 samples$243,750
$243,750–$243,750 typical
Seattle
8 samples$216,000
$205,125–$218,700 typical
Menlo Park
7 samples$235,000
$224,000–$243,750 typical
San Francisco Bay Area
7 samples$220,500
$208,000–$234,000 typical
Live opportunity layer
Senior Software Engineer Machine Learning jobs in Mountain View
Senior Software Engineer, Video Streaming
Mountain View, California
Senior Software Engineer, Networking & Real-Time Systems
Mountain View, California
Senior Software Engineer, Sensor Platform
Mountain View, California
Senior Software Engineer, Devices Platform
Mountain View, California
Senior Software Engineer, Perception ML Data
Mountain View, California (HQ)
Staff/Senior Software Engineer, Onboard Infrastructure
Mountain View, California
Senior Software Engineer, Perception Data Infrastructure
Mountain View, California
Senior Software Engineer, Video Streaming
Mountain View, California (HQ)
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.
Next actions