In [14]: # california_state.ipynb
Abstract
On the official wage series, California pays $141,590 at the median for SOC 15-2051 Data Scientists and $174,410 for SOC 15-1252 Software Developers: rank 2 and rank 1 respectively among the states where BLS publishes a median [1]. The Bay Area anchors the distribution, with senior (L5-equivalent) total compensation commonly $290,000 to $450,000 and frontier-lab packages frequently exceeding $500,000, though those are market-comp figures rather than published wages [2]. State income tax tops out at 13.3 percent for high earners (with a 1 percent Mental Health Services Tax on income above $1,000,000), so all-in tax planning matters more than in no-income-tax states like Washington or Texas. We break the distribution by metro and add headline state-tax math.
1 BLS Occupational Employment and Wage Statistics, May 2025, SOC 15-2051. Snapshot taken 6 September 2026. BLS Occupational Employment and Wage Statistics, May 2025, SOC 15-1252. Snapshot taken 6 September 2026. Public domain; attribute to the Bureau of Labor Statistics. There is no BLS occupation called machine learning engineer, so these two SOCs are the closest published series, not a survey of the job title.
2 Metro bands and total-comp figures are market-comp self-report, not BLS. Source: Levels.fyi Machine Learning Engineer track, region filters captured May 2026. Tax figures: California Franchise Tax Board 2025 rate schedules.
Occupation mapping
"Machine learning engineer" is not a Standard Occupational Classification title, so the BLS Occupational Employment and Wage Statistics survey publishes no wage series under that name. The figures on this page come from SOC 15-2051 Data Scientists, the closest published occupation. Read them as a floor and a shape for the market, not as a Machine learning engineer salary survey.
O*NET OnLine's occupation keyword search returns 15-2051.00 Data Scientists as the first match for the job title "machine learning engineer" (onetonline.org/find/quick?s=machine%20learning%20engineer, checked 6 September 2026).
Software Developers is the other SOC that absorbs machine learning engineering work. It is shown alongside Data Scientists so the bracket is visible rather than hidden behind a single choice.
table ca-1 : base by metro and level
California is not one labour market. Bay Area ML compensation is shaped by the concentration of T1 frontier AI labs and T2 hyperscalers, both of which lean heavily on equity grants tied to high-multiple valuations. Los Angeles supports a sizable autonomous-vehicle and entertainment-tech cluster but lacks the equity density of San Francisco. San Diego is dominated by a single large employer in mobile and AI silicon, plus a biotech-ML cluster around UCSD. Sacramento and the Central Valley are mostly state-government and agriculture-tech adjacent, with very few frontier-lab or hyperscaler outposts. The result is a four-tier intra-state distribution with a roughly 40 percent spread between the top and bottom metros for the same level.
| Metro | L3 base | L5 base | L6 base | L5 total comp |
|---|---|---|---|---|
| San Francisco / Bay AreaT1 frontier labs, T2 hyperscalers, quant outposts concentrated | $155k | $215k | $275k | $290k - $450k+ |
| Los AngelesEntertainment-tech, defense, autonomous-vehicle ML | $135k | $185k | $235k | $210k - $300k |
| San DiegoQualcomm AI, biotech-ML, defence-adjacent | $125k | $170k | $215k | $185k - $260k |
| Sacramento / Central ValleyState government, agtech, fewer T1 / T2 employers | $110k | $150k | $185k | $155k - $215k |
Figure ca-1. California metro base-salary bands and L5 total compensation. These are illustrative market-comp bands from Levels.fyi region filters captured May 2026. They are NOT BLS figures and contain no BLS component; the published California wages sit in section 5 below, separately sourced. Individual offers vary substantially with employer tier and specialisation.
table ca-2 : 2025 brackets (single)
California has the highest top marginal state income tax in the United States. For an ML engineer earning a typical $250,000 base, the effective state income tax rate is approximately 8 to 9 percent. At total compensation levels above $1,000,000 (achievable at frontier labs or quant firms), the additional 1 percent Mental Health Services Tax applies, lifting the top marginal to 13.3 percent on income above $1,000,000. The interaction with federal AMT, ISO exercise treatment, and RSU vesting calendars makes equity-heavy California compensation materially harder to plan around than equivalent comp in no-state-tax states.
California 2025 state income tax brackets (single filer)
| $0 - $11,079 | 1.0% |
| $11,079 - $26,264 | 2.0% |
| $26,264 - $41,452 | 4.0% |
| $41,452 - $57,542 | 6.0% |
| $57,542 - $72,724 | 8.0% |
| $72,724 - $371,479 | 9.3% |
| $371,479 - $445,771 | 10.3% |
| $445,771 - $742,953 | 11.3% |
| $742,953+ | 12.3% |
| $1M+ surcharge | +1.0% Mental Health Services Tax |
Source: California Franchise Tax Board, 2025 Tax Rate Schedules (Schedule X). Married filing jointly thresholds are double. 2026 schedules publish in late 2026.
Worked example: $250,000 base in San Francisco
Simplified calculation: ignores 401(k), HSA, ISO exercise, RSU vesting timing, and any equity component. Equity vesting can lift the effective marginal rate substantially in the year of a large vesting event.
figure ca-2 : compounding
California (specifically the San Francisco Bay Area) is the only metro in the world where a senior ML engineer can routinely access total compensation packages above $500,000, and not by working harder or with more impressive credentials than peers elsewhere. The mechanism is equity at scale. Three concentric reasons explain why.
First, T1 frontier AI labs (foundation-model companies) are mostly headquartered in San Francisco proper or Mountain View. Their pre-IPO equity, granted on a 4-year vest, is currently valued on the basis of $30 billion to $300 billion paper valuations. At a $50 billion valuation with a 0.05 percent grant, that is $25,000,000 in paper value vesting over 4 years. Even a 90 percent valuation haircut at eventual IPO leaves $2.5 million. Senior IC offers from T1 labs in 2024 to 2026 have included grants in this range, with the trade-off that the entire upside is contingent on the lab continuing as a going concern.
Second, T2 hyperscalers (trillion-dollar public platform companies) headquartered in the Bay Area have run an arms race on RSU refresh grants since 2022 to retain ML talent that otherwise leaves for T1 labs. A senior L5 ML engineer with a 4-year initial RSU grant of $400,000 plus annual refresh of $100,000 to $200,000 is now common at the largest two or three hyperscalers. At public-company-stable share prices, this is realised cash, not paper.
Third, San Francisco quant trading firm outposts pay the largest cash bonuses in the city. A senior quant ML researcher at a systematic trading fund in San Francisco can earn $500,000 to $1,500,000 in performance-tied cash bonus on top of a $250,000 to $400,000 base. The bonus is cash and the partner track is a potential long-run upside, but there is no equity grant.
The cost of accessing this equity story is rent, taxes, and the implicit cost of living within commuting distance of San Francisco and Mountain View. Median two-bedroom rent in the Bay Area in 2026 remains above $4,500 per month, and California state income tax at $250,000 to $400,000 is meaningfully above the equivalent in Washington, Texas, or Florida.
The math: a Bay Area $300,000 base plus $150,000 equity (T2 hyperscaler L5) returns approximately the same take-home cash as a $260,000 base plus $130,000 equity in Seattle (T2 L5), once California state income tax and Washington's lack of state income tax are accounted for. But the Bay Area resident also has access to T1 frontier-lab equity that does not exist in Seattle, plus the option to switch employers without relocating. The structural premium is real; the after-tax delta is smaller than the headline numbers suggest.
section ca-3 : non-Bay metros
Los Angeles supports a distinct ML labour market shaped by three industry concentrations: autonomous-vehicle and aerospace (with significant ML hiring at major OEMs and defence primes), entertainment technology (production-pipeline ML and content recommendation at streaming platforms), and a fast-growing AI-startup cluster centred on Pasadena and Santa Monica. LA L5 base ranges $180,000 to $210,000 with total compensation $210,000 to $300,000, roughly 12 to 18 percent below the Bay Area baseline at the same level. Equity grants are smaller and less frequently refreshed because the dominant employers are public companies with lower share-price growth than the Bay Area pre-IPO unicorns.
San Diego is dominated by Qualcomm (which has significantly expanded its AI organisation since 2023), biotech-ML around UCSD spinouts, and a defence-adjacent ML cluster (including ML-for-satellite work). San Diego L5 base falls in the $165,000 to $190,000 range with total compensation $185,000 to $260,000. The metro lacks T1 frontier-lab presence entirely. Compared to the Bay Area, San Diego trades roughly 25 to 35 percent lower nominal compensation for materially lower rent and a better climate; the after-tax purchasing-power gap closes to 15 to 20 percent.
Both LA and San Diego are net importers of ML talent who relocated from the Bay Area for lifestyle reasons. The trade-off is real: an LA L5 ML engineer at a major streaming platform earning $250,000 total compensation can afford a single-family home in a way that a Bay Area equivalent at $350,000 typically cannot. The closer the compensation is to base-only (rather than equity-heavy), the smaller the relocation penalty.
section ca-4 : official wage data
The Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) programme publishes California-specific wage data annually for SOC codes 15-2051 (Data Scientists) and 15-1252 (Software Developers). ML engineer is not a SOC code, so these adjacent categories are the best public wage sources. The BLS California state-level page reports a 15-2051 median annual wage of $141,590 and a 90th percentile of $224,920, over 39,310 jobs. The 15-1252 figures for California are higher on both counts: median $174,410, 90th percentile $272,670, across 284,390 jobs. Market-comp self-report puts ML engineer compensation above both, which is consistent with a tighter labour supply and heavier equity packaging, but that is a self-report claim rather than something the wage series shows.
| California, May 2025 | 15-2051 | 15-1252 |
|---|---|---|
| Median annual | $141,590 | $174,410 |
| Mean annual | $156,000 | $186,770 |
| 25th percentile | $103,360 | $136,990 |
| 75th percentile | $186,820 | $216,670 |
| 90th percentile | $224,920 | $272,670 |
| Employment | 39,310 | 284,390 |
Table ca-3. BLS Occupational Employment and Wage Statistics, May 2025, SOC 15-2051. Snapshot taken 6 September 2026. BLS Occupational Employment and Wage Statistics, May 2025, SOC 15-1252. Snapshot taken 6 September 2026. Public domain; attribute to the Bureau of Labor Statistics. California ranks 2 of 49 published states on 15-2051 and 1 of 50 on 15-1252.
Within California the wage gradient runs from the Bay Area down through Los Angeles and San Diego to the Central Valley, but this site carries the OEWS state file rather than the metropolitan-area file, so it publishes no MSA ranking. The metro splits in section 1 are market-comp bands, not BLS metro estimates. For the official metro tables, read the San Francisco and San Jose MSA pages at BLS directly.
A caveat: BLS OEWS captures W2 wage data, which usually excludes equity (RSU vesting is reported as wage in the year of vesting, so the data does include some equity-driven inflation but lagged). The true total-compensation distribution in the Bay Area is meaningfully wider in the upper tail than OEWS suggests, because equity-vesting events are concentrated in a small number of high earners. Levels.fyi and Blind self-report data captures this tail better, but with self-selection bias toward higher-compensated respondents.
section ca-5 : common questions
How much does an ML engineer make in California?
The official wage answer for California, from the May 2025 BLS OEWS release: SOC 15-2051 Data Scientists has a California median annual wage of $141,590 and SOC 15-1252 Software Developers $174,410. Neither is a machine learning engineer series, because BLS publishes none. On the metro bands this site carries from market-comp self-report, which are not BLS figures, San Francisco Bay Area senior (L5-equivalent) base falls in the $195,000 to $230,000 range, with total compensation often $290,000 to $450,000 once equity is included. Los Angeles and San Diego sit roughly 10 to 15 percent below the Bay Area baseline.
Why does the Bay Area pay so much more than other California metros?
Three structural reasons. First, the Bay Area concentrates almost every T1 frontier AI lab and most T2 hyperscaler ML organisations. Second, equity grants tied to pre-IPO or trillion-dollar-market-cap valuations are larger and more frequently refreshed. Third, the local labour market for foundation-model and LLM expertise is tight, pushing offers above the levels seen in markets where the buyer is a single anchor employer.
What is the after-tax take-home for a $250,000 California ML engineer?
On a $250,000 base in 2026, California state income tax alone is approximately $20,000 to $22,000 (effective rate around 8 to 9 percent at this income), with the top marginal rate of 9.3 percent applying above $72,724 for a single filer. Federal income tax, FICA, and (for $1M+ earners) the additional Mental Health Services Tax push total all-in income tax above 35 percent. Equity-heavy compensation requires careful planning around RSU vesting and AMT.
Does California pay better than Washington for ML engineers after tax?
Generally no. On the official wage series Washington is ahead before tax is even considered: the May 2025 OEWS median for SOC 15-2051 Data Scientists is $163,350 in Washington against $141,590 in California. Washington then adds no state income tax, so a $250,000 base in Seattle returns roughly $15,000 to $20,000 more take-home than the same base in San Francisco. California's advantage shows up in total compensation rather than wages: equity grants from frontier labs and pre-IPO unicorns that mostly do not exist in Seattle, and which OEWS captures only when the equity vests as W2 wage.
Is the Bay Area cost of living worth the salary premium?
On a purchasing-power basis, Bay Area ML salaries are 30 to 40 percent higher than cost-of-living-equivalent salaries in Austin or Denver. The compounding factor is equity: a $300,000 T2 hyperscaler package in the Bay Area can generate substantially more wealth over four years than a $160,000 base elsewhere. For frontier-lab employees, the equity component can dwarf the cost-of-living delta. For traditional-enterprise ML engineers in California, the cost-of-living math is much less favourable.
Which California ML employers tend to pay the most?
Frontier AI labs headquartered in San Francisco lead, with total compensation reportedly $500,000 to $2,000,000-plus for senior to staff levels (per anonymised Levels.fyi entries). Trillion-dollar hyperscalers with major Bay Area campuses pay $280,000 to $700,000 total compensation at L5 to L6. AI-focused unicorns ($170,000 to $260,000 base, $260,000 to $520,000 total comp) and quant trading firms with SF outposts ($200,000 to $350,000 base, $350,000 to $1,000,000-plus cash) round out the top tier.
Are California ML engineer salaries growing?
This site cannot answer that from the BLS data it carries. It holds a single OEWS vintage, May 2025, so no year-over-year change can be computed from it, and we do not publish a growth rate we cannot derive. What the May 2025 release does show for California is the shape of the upper tail: SOC 15-2051 Data Scientists has a state median of $141,590 against a 90th percentile of $224,920, and SOC 15-1252 Software Developers a median of $174,410 against a 90th percentile of $272,670. Reports of a 20 to 40 percent lift in frontier-lab compensation after 2023 come from market-comp self-report and press coverage, not from BLS.
San Francisco Bay Area deep dive
The metro that anchors California ML compensation
Washington state
No state income tax. How the math actually compares
Frontier AI lab tier
Why T1 labs concentrate in California
Total compensation breakdown
Base vs RSU vs bonus across tiers
All states ranked
Cost-of-living-adjusted rankings
Offer negotiation playbook
California-specific tactics for equity-heavy offers
In [ ]: # reader_questions.ipynb
Write in. A person opens every message, and the ones we can answer come back with the survey release or the public disclosure the number is drawn from, stated plainly enough that you can go and check it. We put no clock on a reply. Should an answer be worth reading twice we might set it out here stripped of anything identifying, and we will write and ask you before that happens.
Out[ ]:
Treat everything on this site as compensation reference assembled from published surveys and public filings, not as financial advice and not as a benchmark any single negotiation should be anchored to. Your own offer turns on the employer, the level it is pitched at, the equity instrument behind it and the market on the day it is made.