$187,500
mediana · por año, USD anualizado
$195,000
mediana · por año, USD anualizado
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
Platform Engineer
Senior Staff+ Software Engineer, Kubernetes Platform
Staff+ Infrastructure Engineer, Cluster Infrastructure
Software Engineer, Research Infrastructure
Senior Security Platform Engineer I
Principal .NET Software Engineer - Cloud Payments Platform
Principal .NET Software Engineer- Cloud Payments Platform
Staff+ Software Engineer, Safeguards Infrastructure
Software Engineer, Platform
SOC Emulation Engineer - Hardware Emulation Infrastructure
| 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 |
| Empresa | Mediana | Puestos |
|---|---|---|
Speechify
|
$170,000 | 103 |
OpenAI
|
$308,250 | 28 |
Nuro
|
$200,450 | 24 |
Palantir
|
$167,500 | 24 |
Databricks
|
$225,000 | 21 |
Coinbase
|
$202,483 | 20 |
Reddit
|
$244,500 | 18 |
Anduril Industries
|
$222,000 | 18 |
| Ubicación | Mediana | Puestos |
|---|---|---|
| San Francisco | $228,500 | 413 |
| Seattle | $214,250 | 110 |
| New York | $210,000 | 320 |
| Austin | $202,500 | 39 |
| Los Angeles | $187,500 | 31 |
| Boston | $185,000 | 64 |
| Toronto | $185,000 | 61 |
| Chicago | $183,000 | 22 |
| Denver | $180,000 | 29 |
| Atlanta | $170,000 | 10 |
La mediana de MLOps es de $187,500 por año (normalmente $147,500–$236,325), frente a $195,000 de Platform Engineer ($166,525–$230,000). Eso pone a Platform Engineer alrededor de un 4% 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 MLOps y Platform Engineer 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.