$190,000
mediana · por año, USD anualizado
$187,500
mediana · por año, USD anualizado
Platform Engineer
Senior Staff+ Software Engineer, Kubernetes Platform
Senior Security Platform Engineer I
Principal .NET Software Engineer - Cloud Payments Platform
Principal .NET Software Engineer- Cloud Payments Platform
Software Engineer, Platform
Infrastructure and Platform Development Engineer
Agent Platform Engineer
Principal Engineer, AI Platform
Member of Technical Staff (Software Engineer, Inference & Training Platform)
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
| Empresa | Mediana | Puestos |
|---|---|---|
Accenture Federal Services
|
$151,800 | 29 |
Air Apps
|
$65,184 | 22 |
Captivation Software
|
$200,000 | 21 |
Reddit
|
$244,500 | 18 |
Anduril Industries
|
$222,000 | 15 |
Coinbase
|
$202,483 | 15 |
Airwallex
|
$162,878 | 13 |
Roblox
|
$265,138 | 12 |
| Empresa | Mediana | Puestos |
|---|---|---|
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 |
| Ubicación | Mediana | Puestos |
|---|---|---|
| San Francisco | $225,500 | 250 |
| Seattle | $212,500 | 62 |
| New York | $210,000 | 209 |
| Los Angeles | $200,650 | 18 |
| Austin | $198,900 | 27 |
| Chicago | $195,000 | 31 |
| Denver | $186,000 | 26 |
| Boston | $182,500 | 59 |
| Toronto | $165,000 | 50 |
| Atlanta | $161,500 | 10 |
La mediana de DevOps es de $190,000 por año (normalmente $151,040–$225,000), frente a $187,500 de MLOps ($147,500–$236,325). Eso pone a DevOps alrededor de un 1% por delante en la mediana.
Ambas cifras se calculan en vivo a partir de ofertas activas en JobsRadar y se normalizan a USD anualizado, de modo que DevOps y MLOps se comparan en igualdad de condiciones independientemente de la moneda en la que se publicó originalmente cada puesto. Solo los puestos que publican un rango salarial alimentan las medianas; las cifras se actualizan cada pocas horas a medida que se publican nuevos puestos y se cierran los antiguos, así que esta comparación refleja el mercado actual y no una encuesta fija. Úsala como referencia orientativa al sopesar un camino frente a otro.