NLP Engineer: market
An NLP Engineer builds systems that understand and generate text: classification, entity extraction, search, chatbots and large language model solutions — from data and training to shipping the model into the product. We currently track 40 open positions for this role, 37 of them fresh. The core is Python, PyTorch, Hugging Face libraries, transformers and embeddings, working with LLMs (prompting, fine-tuning, RAG), vector databases, model evaluation and MLOps basics. By co-occurrence in requirements, Python, LLM, AWS and JavaScript appear most often. 46% of the postings allow fully remote work. Below is a live slice of the NLP Engineer market: geography, seniority, adjacent stack and sources.
The NLP Engineer market currently has 40 open roles, 37 of them freshly observed.
46% of NLP Engineer postings allow fully remote work; the share counts only postings that state the format.
⚠ salary known for 1 of 40 jobs; remote share from 35 with a stated format; 37 counted as fresh observations; trend and hiring difficulty are not shown
Timeline: postings and sources
How many NLP Engineer postings appeared each week since 4 May, and from how many sources. The second line separates market growth from coverage growth: a jump in the week new sources were connected means we started seeing more, not that the market grew.
New postings and active sources per week
Sources over the period: 46
New sources connected: 18 May +1 · 8 Jun +2 · 15 Jun +1 · 22 Jun +6 · 29 Jun +3 · 6 Jul +4 · 13 Jul +4 · 3 Aug +2 · 10 Aug +1 · 17 Aug +1 · 24 Aug +2 · 14 Sept +5 · 21 Sept +3 · 28 Sept +5 · 5 Oct +3 · 12 Oct +3
Week = posting first-seen date, all statuses; postings are selected by the same rule as this page's counter. Sources are distinct collection channels; their names are not published.
Demand and observed supply: NLP Engineer
| Open demand | 40 |
| Observed supply | — not published |
⚠ candidates matching a vacancy are not counted yet: demand and the observed pool are shown
Salary distribution: NLP Engineer
The range histogram for NLP Engineer uses only postings with an explicit compensation range; the median is computed over the same sample.
The chart will appear once enough observations accumulate for this breakdown.
Demand geography: NLP Engineer
| country | jobs |
|---|---|
| PL | 6 |
| US | 6 |
| IN | 6 |
| RU | 3 |
| GB | 3 |
| CO | 2 |
| SA | 1 |
| CA | 1 |
| KZ | 1 |
| GR | 1 |
The top country for NLP Engineer demand is Poland (6 positions).
⚠ job counts only: salary by country is not published
Used together with
In NLP Engineer requirements the most frequently named skills and technologies are Python, LLM, AWS and JavaScript.
Demand by grade: NLP Engineer
| grade | jobs |
|---|---|
| senior | 9 |
| middle | 6 |
| lead | 6 |
| junior | 1 |
Senior-and-above is about 68% of 22 NLP Engineer postings with an explicit grade.
⚠ demand side only: the grade of the observed pool is unknown for most of it
Employers: NLP Engineer
Demand is spread across 23 employers. The largest accounts for 10.8%, the top ten for 64.9%; the remaining 35.1% is long tail.
| share | value |
|---|---|
| top-1 | 10.8% |
| top-3 | 27.0% |
| top-10 | 64.9% |
| long tail | 35.1% |
NLP Engineer openings come from 23 distinct employers.
⚠ names are not shown: staffing agencies and end employers are not yet told apart by the classifier
Where Zorky sees this market
Observed across 18 sources; the largest accounts for 25.0% — this market does not rest on a single channel.
NLP Engineer postings arrive mostly from ATS & career sites and job boards & aggregators.
Recent openings: NLP Engineer
- Senior Machine Learning Engineer (NLP/LLMs) · SA
- ML-разработчик (NLP/LLM) · RU
- Computational Linguist with Slovenian · PL
- Computational Linguist with Czech or Slovenian · PL
- Computational Linguist with Turkish · PL
- Conversational AI Engineer - Google/GECX & Code Agents · CO
- Computational Linguist with Slovenian · PL
- Applied AI + NLP Engineer · US
Adjacent markets
⚠ adjacent markets for comparison are not defined yet
How this is measured
- Vacancy
- an open job that cleared the quality gate and lists at least two technologies
- Observed candidate
- a candidate whose stack contains this technology; an aggregate — not a single record leaves the perimeter
- Matchable candidate
- not counted yet
- Window
- jobs open at the moment the snapshot was built
About the data
- Some breakdowns are hidden: their data coverage is not yet sufficient.
- Statistics are shown only where the sample clears a quality gate.
- A missing block does not mean a value of zero.
Breakdowns currently hidden: 9.
Data as of 2026-10-24
Frequently asked questions
Common questions about the NLP Engineer role — short answers from the same data slice.
What does an NLP Engineer do?
An NLP Engineer builds systems that understand and generate text: classification, entity extraction, search, chatbots and large language model solutions — from data and training to shipping the model into the product.
Which skills do NLP Engineer postings require?
The core is Python, PyTorch, Hugging Face libraries, transformers and embeddings, working with LLMs (prompting, fine-tuning, RAG), vector databases, model evaluation and MLOps basics. In the current slice, Python, LLM, AWS and JavaScript appear in requirements most often.
Does an NLP engineer need to train models from scratch?
Rarely: most tasks are solved by fine-tuning and adapting existing models. It matters more to collect data, measure quality honestly and get the model into the product.
How remote-friendly are NLP Engineer jobs?
46% of postings with an explicit format allow fully remote work; the slice tracks 40 open positions.
Get the full NLP Engineer market details
Full role analytics — salary bands, employers, trends and available candidates. Leave a contact and we'll send the details.