ML Engineer: market
An ML Engineer takes machine-learning models to production: training and fine-tuning, inference optimization, data pipelines for models and quality monitoring after release. We currently track 2 720 open positions for this role, 2 604 of them fresh. The core is Python, PyTorch, data work, MLOps tools (MLflow, Kubeflow), Docker and Kubernetes, cloud GPUs; LLM postings add fine-tuning and model serving (vLLM, Triton). By co-occurrence in requirements, Python, LLM, PyTorch and AWS appear most often. 34% of the postings allow fully remote work. Below is a live slice of the ML Engineer market: geography, seniority, adjacent stack and sources.
The ML Engineer market currently has 2,720 open roles, 2,604 of them freshly observed. Median salary $11,820/mo.
34% of ML Engineer postings allow fully remote work; the share counts only postings that state the format.
⚠ salary known for 229 of 2720 jobs; remote share from 2374 with a stated format; 2604 counted as fresh observations; trend and hiring difficulty are not shown
Timeline: postings and sources
How many ML 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: 194
New sources connected: 11 May +7 · 18 May +3 · 25 May +3 · 1 Jun +6 · 8 Jun +5 · 22 Jun +13 · 29 Jun +28 · 6 Jul +17 · 13 Jul +18 · 20 Jul +10 · 27 Jul +6 · 3 Aug +2 · 10 Aug +7 · 17 Aug +2 · 24 Aug +4 · 31 Aug +7 · 7 Sept +4 · 14 Sept +4 · 21 Sept +11 · 28 Sept +2 · 5 Oct +10 · 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.
Salaries over time
Median ML Engineer salary per week, USD per month.
Median salary, USD per month
Only postings with a USD salary and a known period (month or year), $500–$50,000 per month. Weeks with fewer than 10 such postings are left blank — that means no data, not zero.
Remote work over time
Share of ML Engineer postings offering fully remote work, per week.
Remote postings, %
The share is among postings that state a format (remote, hybrid, office). Weeks with fewer than 10 such postings are left blank.
Technologies over time
How the share of ML Engineer postings mentioning each of the top technologies changed.
Postings mentioning the technology, %
Share among postings with a tagged stack; the series starts on 10 Aug: earlier stack tags were assigned differently. Weeks with fewer than 20 tagged postings are left blank.
Countries over time
How the share of ML Engineer postings in each of the top countries changed, per week.
Postings in the country, %
Share among postings with a known country; the chart shows the five countries with the most postings over six months. Weeks with fewer than 20 postings with a known country are left blank. A rising share can mean a newly connected source in that country rather than market growth.
Demand and observed supply: ML Engineer
| Open demand | 2,720 |
| Observed supply | — not published |
⚠ candidates matching a vacancy are not counted yet: demand and the observed pool are shown
Salary distribution: ML Engineer
One in ten earns under $4,728, one in ten over $20,833. Half the market falls between $6,375 and $16,666. Sample: 229.
The range histogram for ML Engineer uses only postings with an explicit compensation range; the median is computed over the same sample.
Demand geography: ML Engineer
| country | jobs |
|---|---|
| US | 918 |
| GB | 309 |
| PL | 153 |
| IN | 122 |
| SG | 108 |
| DE | 105 |
| CA | 82 |
| FR | 55 |
| RU | 44 |
| NL | 39 |
The top country for ML Engineer demand is the US (918 positions).
⚠ job counts only: salary by country is not published
Used together with
In ML Engineer requirements the most frequently named skills and technologies are Python, LLM, PyTorch and AWS.
Demand by grade: ML Engineer
| grade | jobs |
|---|---|
| senior | 980 |
| principal | 445 |
| lead | 151 |
| middle | 67 |
| junior | 49 |
Senior-and-above is about 93% of 1 692 ML Engineer postings with an explicit grade.
⚠ demand side only: the grade of the observed pool is unknown for most of it
Employers: ML Engineer
Demand is spread across 1,211 employers. The largest accounts for 3.4%, the top ten for 15.1%; the remaining 84.9% is long tail.
| share | value |
|---|---|
| top-1 | 3.4% |
| top-3 | 7.4% |
| top-10 | 15.1% |
| long tail | 84.9% |
ML Engineer openings come from 1 211 distinct employers; the largest one accounts for only 3.4% of postings — the market is not tied to a single hirer.
⚠ names are not shown: staffing agencies and end employers are not yet told apart by the classifier
Where Zorky sees this market
Observed across 100 sources; the largest accounts for 23.2% — this market does not rest on a single channel.
ML Engineer postings arrive mostly from ATS & career sites and job boards & aggregators.
Recent openings: ML Engineer
- Machine Learning Engineer Co-op · CA
- Senior / Staff Machine Learning Engineer, Apple Cloud AI Platform · US
- Machine Learning Engineer · US
- Senior Machine Learning Engineer (NLP/LLMs) · SA
- Staff Machine Learning Engineer
- (Senior) ML Engineer - Computer Vision (f/m/d)
- Senior Machine Learning Engineer · GB
- Machine Learning Engineer-Xumo · US · $13,869
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: 8.
Data as of 2026-10-24
Frequently asked questions
Common questions about the ML Engineer role — short answers from the same data slice.
What does an ML Engineer do?
An ML Engineer takes machine-learning models to production: training and fine-tuning, inference optimization, data pipelines for models and quality monitoring after release.
Which skills do ML Engineer postings require?
The core is Python, PyTorch, data work, MLOps tools (MLflow, Kubeflow), Docker and Kubernetes, cloud GPUs; LLM postings add fine-tuning and model serving (vLLM, Triton). In the current slice, Python, LLM, PyTorch and AWS appear in requirements most often.
How does an ML Engineer differ from a Data Scientist?
A Data Scientist researches and builds the model; an ML Engineer makes it work reliably in the product — with pipelines, versioning, monitoring and acceptable latency.
How remote-friendly are ML Engineer jobs?
34% of postings with an explicit format allow fully remote work; the slice tracks 2 720 open positions.
Get the full ML Engineer market details
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