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Google Gemini (Vertex AI)

Google’s family of multimodal models, reached through the Gemini API or Vertex AI on Google Cloud.

Hiring data as of September 20, 2026 · refreshed daily

companies naming it
9 of 47companies naming it
open roles naming it
20open roles naming it
of those based in NYC
16of those based in NYC
median posted base (n=9)
$251kmedian posted base (n=9)

What Google Gemini means

Gemini is Google’s model family, notable for long context windows and native handling of images, audio, and video. Enterprises typically reach it through Vertex AI, Google Cloud’s managed AI platform, which is why we count Vertex AI mentions under the same term.

Google Gemini in New York job posts

9 of the 47 New York AI companies we track name Google Gemini in at least one open role today, across 20 postings. 16 of those are based in New York; the rest are remote or in the companies’ other offices.

This is engineering vocabulary: 70% of the postings that name it are Engineering roles.

Headway alone accounts for 8 of the 20 postings, which is why we lead with the company count: one employer’s hiring push should not read as a market trend.

How to read it

Named less often than OpenAI or Anthropic in New York startup postings, and frequently in the same sentence as both. A posting that lists all three describes a multi-provider stack where model choice is an engineering decision made per task.

What these roles pay

$215k25th percentile
$251kMedian
$296k75th percentile

Midpoints of 9 distinct salary ranges posted on New York roles that name Google Gemini. Base salary only; on-target earnings are excluded, and a range repeated across one company’s postings counts once. For comparison, the median across all New York engineering postings is $215k. A term’s pay reflects the roles that name it as much as the skill itself — see the role mix below before reading a premium into it. Full bands by function and seniority are in the NYC salary calculator.

Companies naming Google Gemini, daily

Count of companies with at least one open role naming the term. We read between 47 and 48 companies a day over this period, so a move of one or two is noise.

07.5159Aug 17Sep 20Aug 17: 9 companiesAug 18: 9 companiesAug 19: 9 companiesAug 20: 9 companiesAug 21: 9 companiesAug 22: 9 companiesAug 23: 9 companiesAug 24: 9 companiesAug 25: 9 companiesAug 26: 8 companiesAug 27: 8 companiesAug 28: 8 companiesAug 29: 8 companiesAug 30: 8 companiesAug 31: 8 companiesSep 1: 8 companiesSep 2: 8 companiesSep 3: 8 companiesSep 4: 8 companiesSep 5: 8 companiesSep 6: 8 companiesSep 7: 8 companiesSep 8: 8 companiesSep 9: 8 companiesSep 10: 8 companiesSep 11: 8 companiesSep 12: 8 companiesSep 13: 8 companiesSep 14: 8 companiesSep 15: 8 companiesSep 16: 8 companiesSep 17: 8 companiesSep 18: 8 companiesSep 19: 9 companiesSep 20: 9 companies
View as table
Datecompanies
2026-08-179
2026-08-189
2026-08-199
2026-08-209
2026-08-219
2026-08-229
2026-08-239
2026-08-249
2026-08-259
2026-08-268
2026-08-278
2026-08-288
2026-08-298
2026-08-308
2026-08-318
2026-09-018
2026-09-028
2026-09-038
2026-09-048
2026-09-058
2026-09-068
2026-09-078
2026-09-088
2026-09-098
2026-09-108
2026-09-118
2026-09-128
2026-09-138
2026-09-148
2026-09-158
2026-09-168
2026-09-178
2026-09-188
2026-09-199
2026-09-209

Who names it

Open roles naming Google Gemini, by company.

  • Headway8
  • Hebbia4
  • K Health2
  • Comet1
  • ElevenLabs1
  • EvolutionIQ1
  • Grow Therapy1
  • Maven Clinic1
  • Patlytics1

Which roles

The same postings, by function and by seniority.

  • Engineering14
  • Operations4
  • Other2
  • Mid8
  • Senior5
  • Staff/Principal4
  • Manager2
  • Director1

Named alongside Google Gemini

Terms that appear in the same postings far more often than chance would put them there. The number is how many of the 9 companies pair the two.

Open roles naming Google Gemini

A sample from today’s data, New York roles first and one per company before any repeats. Links go to the employer’s own posting. For the full market, see AI jobs in NYC.

How this is counted

Every day we read the open roles on the public job boards of the New York AI companies in our coverage — the NYC AI 100 and the AI in NYC Show roster. This term is matched against each role’s description after removing the text a company repeats across its postings, so an “About us” paragraph cannot tag every role the company has open. A vendor’s own postings never count toward its own name.

The figure means named in a job posting. It does not mean used in production, and a “nice to have” counts the same as a requirement. Companies are the headline number because posting counts are dominated by whichever few employers are hiring hardest this month.

Full method, including the pay rules, is on the glossary index; the underlying series is the NYC AI Hiring Index.

Google Gemini — common questions

What does Google Gemini mean in an AI job posting?

Google’s family of multimodal models, reached through the Gemini API or Vertex AI on Google Cloud. Named less often than OpenAI or Anthropic in New York startup postings, and frequently in the same sentence as both. A posting that lists all three describes a multi-provider stack where model choice is an engineering decision made per task.

How many New York AI companies are hiring for Google Gemini?

As of September 20, 2026, 9 of the 47 New York AI companies we track name Google Gemini in the description of at least one open role, across 20 postings (16 based in New York). The count refreshes daily from the companies’ own job boards.

What do roles that ask for Google Gemini pay in New York?

Across 9 distinct posted salary ranges on New York roles naming Google Gemini, the median midpoint is $251k base, with the middle half between $215k and $296k. The same figure for all New York engineering postings is $215k. These are employer-posted ranges required by New York’s pay transparency law, base salary only.

Which skills are asked for alongside Google Gemini?

In the same postings, the terms most distinctively paired with Google Gemini are OpenAI, Anthropic, BigQuery, Vector search, LangChain. We rank pairings by how much more often they appear together than apart, so near-universal terms such as Python do not crowd out the informative ones.

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