Side-by-side distribution
MLOps
$187,500
median · per year, annualized USD
- Disclosing
- 18.9%
- Live roles
- 127
Prompt Engineer
$197,500
median · per year, annualized USD
- Disclosing
- 31.8%
- Live roles
- 88
Highest-paying jobs
Senior Machine Learning Engineer, DevOps/SRE
Staff Machine Learning Operations Engineer
Senior Data Engineer, MLOps [Remote-US]
Senior, ML Engineer - ML Ops Framework
Senior, ML Engineer - ML Ops Framework
Senior Machine Learning Operations Engineer
Staff ML/LLM Ops Engineer
Sr. Machine Learning Ops Engineer
DoD MLOps Software Engineer
Sr. Machine Learning Ops Engineer
Highest-paying jobs
Machine Learning Engineer, Speech LLM Training - San Francisco
Machine Learning Engineer, Model Evaluations (Speech LLM) - San Francisco
Principal Machine Learning Engineer- LLM Fine-tuning and Optimization
Machine Learning Engineer, Inference & Serving (Speech LLM) - San Francisco
Machine Learning Engineer, LLM Evals & Observability
Machine Learning Engineer, LLM Evals & Observability
Principal LLM Inference Engineer
Staff Attack Engineer, AI/LLM
Staff ML/LLM Ops Engineer
Staff Machine Learning Engineer, CustomerLake (ML/LLM)
Top companies hiring
| Company | Median | Roles |
|---|---|---|
|
Garner Health
|
$297,500 | 2 |
|
Torc Robotics
|
$249,000 | 2 |
|
Quanata
|
$256,500 | 1 |
|
Roku
|
$254,875 | 1 |
|
LVT
|
$242,650 | 1 |
|
Hayden AI
|
$230,000 | 1 |
Instacart
|
$212,750 | 1 |
|
Cimgroup
|
$200,000 | 1 |
Zscaler
Five9
Prompt Engineer salary by location
| Location | Median | Roles |
|---|---|---|
| San Francisco | $250,000 | 7 |
| New York | $197,500 | 3 |
MLOps vs Prompt Engineer: which pays more?
The median for MLOps is $187,500 per year (typically $147,500–$236,325), versus $197,500 for Prompt Engineer ($158,813–$241,325). That puts Prompt Engineer about 5% ahead at the median.
Both figures are computed live from active listings on JobsRadar and normalized to annualized USD, so MLOps and Prompt Engineer are compared on equal terms regardless of the currency each role was originally posted in. Only roles that publish a salary range feed the medians; numbers refresh every few hours as new roles post and older ones close, so this comparison reflects the market right now rather than a fixed survey. Use it as a directional benchmark when weighing one path against the other.