MLOps: market
MLOps is the engineering of the machine-learning model lifecycle: reproducible training, model registry, production rollout, quality and data-drift monitoring. We track 2 127 open positions listing MLOps, 2 040 of them fresh. LLMs widened the role: classic pipelines now come with LLM application evaluation, GPU model serving and inference cost management. Most of the demand comes from ML/AI, AI Engineer and Data roles. It most often appears next to Python, AWS and LLM. 35% of the postings allow fully remote work. Below is measured MLOps demand.
The MLOps market currently has 2,127 open roles, 2,040 of them freshly observed. Median salary $9,850/mo. Observed candidate pool — 353.
35% of MLOps postings allow fully remote work; the share counts only postings that state the work format.
⚠ salary known for 152 of 2127 jobs; remote share from 1706 with a stated format; 2040 counted as fresh observations; trend and hiring difficulty are not shown
Timeline: postings and sources
How many MLOps postings appeared each week since 10 Aug, 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: 141
New sources connected: 17 Aug +16 · 24 Aug +14 · 31 Aug +16 · 7 Sept +7 · 14 Sept +11 · 21 Sept +22 · 28 Sept +10 · 5 Oct +10 · 12 Oct +11
Week = posting first-seen date, all statuses. A posting belongs to the technology by its stack tag; the series starts on 10 Aug 2026 — earlier tags were assigned differently and are not comparable. Sources are distinct collection channels; their names are not published.
Salaries over time
Median MLOps 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 MLOps 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.
Countries over time
How the share of MLOps 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
| Open demand | 2,127 |
| Observed supply | 353 |
⚠ candidates matching a vacancy are not counted yet: demand and the observed pool are shown
Salary distribution
One in ten earns under $4,250, one in ten over $17,916. Half the market falls between $6,090 and $15,416. Sample: 152.
The range histogram for MLOps postings uses only postings with an explicit compensation range; the median is computed over the same sample.
Demand geography
| country | jobs |
|---|---|
| US | 420 |
| PL | 306 |
| GB | 169 |
| IN | 136 |
| DE | 127 |
| FR | 56 |
| CA | 55 |
| RU | 52 |
| SG | 41 |
| BR | 39 |
The top country for MLOps demand is the US (420 positions).
⚠ job counts only: salary by country is not published
Used together with
MLOps most often appears next to Python, AWS and LLM.
Roles that use it
| role | jobs |
|---|---|
| ML/AI | 770 |
| AI Engineer | 434 |
| Data | 279 |
| DevOps | 211 |
| Architect | 140 |
| Platform Engineer | 54 |
| Fullstack | 46 |
| Backend | 34 |
| Product | 25 |
| Security | 19 |
⚠ the `Other` and `IT` buckets are excluded as non-roles
Demand by grade
| grade | jobs |
|---|---|
| senior | 729 |
| principal | 198 |
| lead | 153 |
| middle | 129 |
| junior | 36 |
Senior-and-above is about 87% of 1 245 graded MLOps postings. MLOps requires experience in both ML and infrastructure — junior openings are almost absent.
⚠ demand side only: the grade of the observed pool is unknown for most of it
Employers
Demand is spread across 1,140 employers. The largest accounts for 2.4%, the top ten for 10.6%; the remaining 89.4% is long tail.
| share | value |
|---|---|
| top-1 | 2.4% |
| top-3 | 5.2% |
| top-10 | 10.6% |
| long tail | 89.4% |
⚠ names are not shown: staffing agencies and end employers are not yet told apart by the classifier
Where Zorky sees this market
Observed across 102 sources; the largest accounts for 22.5% — this market does not rest on a single channel.
MLOps postings arrive mostly from ATS & career sites and job boards & aggregators.
Recent openings
- Senior Solutions Architect (VMware & AI Platform)
- (Senior) AI Engineer (m/f/d) · US
- Data Solutions Architect-8293 - Preston · GB
- #EG Data Engineer · SG
- Lead Applied Scientist
- Lead, Machine Learning Operations Engineer
- ML Engineer - Large Molecules
- Forward-Deployed ML Engineer – Cofolding
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: 7.
Data as of 2026-10-23
Frequently asked questions
Common questions about the MLOps market — short answers from the same data slice.
Which tools appear in MLOps postings?
MLflow or Weights & Biases for experiments, orchestrators (Airflow, Kubeflow, Prefect), Kubernetes and Docker, model serving (Triton, vLLM, KServe), cloud ML platforms (SageMaker, Vertex AI, Azure ML), monitoring.
How does MLOps differ from DevOps?
Besides code, data and models are versioned; quality is checked with model metrics, not just tests; production degrades from data drift even without code changes.
How big is MLOps demand?
The slice tracks 2 127 open MLOps positions; demand grows as teams move from experimenting with models to operating them.