Neuronify

LLMs (large language models)

Models trained on very large text corpora to predict the next token, which turns out to be enough to write, summarize, extract, translate, and reason over language.

Hiring data as of September 20, 2026 · refreshed daily

companies naming it
40 of 47companies naming it
open roles naming it
261open roles naming it
of those based in NYC
134of those based in NYC
median posted base (n=81)
$213kmedian posted base (n=81)

What LLMs means

A large language model is a neural network trained to predict the next token in a sequence, at a scale where that single skill generalizes into writing, summarizing, classifying, extracting structured data, and working through multi-step problems. GPT, Claude, Gemini, and Llama are all LLMs. Most companies never train one; they call a provider’s model through an API and build the product around it.

That shift is why the term shows up far outside research teams. Working with LLMs in 2026 mostly means application engineering: choosing a model for the cost and latency you can afford, shaping what goes into the context window, checking outputs, and handling the cases where the model is confidently wrong.

LLMs in New York job posts

40 of the 47 New York AI companies we track name LLMs in at least one open role today, across 261 postings. 134 of those are based in New York; the rest are remote or in the companies’ other offices.

Engineering roles make up 47% of the postings that name it, with the rest spread across other functions.

How to read it

When a posting names LLMs without naming a provider or a technique, it is describing the product surface, not the skill. Read the rest of the description for the real requirement — evals, retrieval, agents, or serving — and expect the interview to probe whether you have shipped something on a model rather than prompted one.

What these roles pay

$175k25th percentile
$213kMedian
$245k75th percentile

Midpoints of 81 distinct salary ranges posted on New York roles that name LLMs. 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.

Trend

We began extracting this term from posting text on September 20, 2026. Job descriptions disappear when a role is filled, so the series cannot be backfilled; a trend line appears here once a week of data exists.

Who names it

Open roles naming LLMs, by company.

Also: Basis, EliseAI, K Health, EvolutionIQ, Grow Therapy, Mirage (fka Captions), SmarterDx, Alloy, Andela, Anterior, Comet, Pinecone, Preql, Rillet, Spade, April, Arthur, DataKind, H1, Hume AI, Hyperscience, Maven Clinic, Norm Ai, Runway, Sixfold, Slingshot AI, Tabs, Vic.ai.

Which roles

The same postings, by function and by seniority.

  • Engineering122
  • GTM60
  • Operations24
  • Product21
  • Research15
  • Other8
  • Mid169
  • Senior49
  • Staff/Principal31
  • Manager6
  • Entry3
  • Director2

Named alongside LLMs

Terms that appear in the same postings far more often than chance would put them there. The number is how many of the 40 companies pair the two.

Open roles naming LLMs

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.

On the AI in NYC Show

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.

LLMs — common questions

What does LLMs mean in an AI job posting?

Models trained on very large text corpora to predict the next token, which turns out to be enough to write, summarize, extract, translate, and reason over language. When a posting names LLMs without naming a provider or a technique, it is describing the product surface, not the skill. Read the rest of the description for the real requirement — evals, retrieval, agents, or serving — and expect the interview to probe whether you have shipped something on a model rather than prompted one.

How many New York AI companies are hiring for LLMs?

As of September 20, 2026, 40 of the 47 New York AI companies we track name LLMs in the description of at least one open role, across 261 postings (134 based in New York). The count refreshes daily from the companies’ own job boards.

What do roles that ask for LLMs pay in New York?

Across 81 distinct posted salary ranges on New York roles naming LLMs, the median midpoint is $213k base, with the middle half between $175k and $245k. 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 LLMs?

In the same postings, the terms most distinctively paired with LLMs are LangChain, RAG, Vector search, Prompt engineering, Tool use. 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.

Need someone who has actually shipped this?

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