$187,500
mediana · por año, USD anualizado
$185,000
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
Senior Business Development Lead - Retail Tech & Software Services
Lead Software Engineer (Backend)
Customer Engineering Lead
Technical Lead, Safety Research
Lead Security Engineer
Data Engineering Lead
Staff Engineer, Emulation Technical Lead
RISC-V AI / HPC & Agentic Software Engineering Lead
Technical Lead Manager, Data Engineering, Trust & Safety
Lead Machine Learning Inference Engineer, Advertising
| 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 |
|---|---|---|
Anduril Industries
|
$170,000 | 33 |
STR
|
$198,250 | 26 |
Motional
|
$237,500 | 21 |
Accenture Federal Services
|
$197,750 | 21 |
Fluidstack
|
$275,000 | 19 |
Scout Motors
|
$176,250 | 16 |
Relativity Space
|
$170,000 | 15 |
OpenAI
|
$338,750 | 14 |
| Ubicación | Mediana | Puestos |
|---|---|---|
| Austin | $266,500 | 24 |
| San Francisco | $238,500 | 141 |
| Seattle | $234,225 | 34 |
| New York | $222,000 | 100 |
| Boston | $212,500 | 51 |
| Atlanta | $190,000 | 13 |
| Denver | $183,500 | 15 |
| Los Angeles | $175,000 | 19 |
| Toronto | $167,673 | 24 |
| Chicago | $166,000 | 26 |
La mediana de MLOps es de $187,500 por año (normalmente $147,500–$236,325), frente a $185,000 de Tech Lead ($152,500–$223,683). Eso pone a MLOps 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 MLOps y Tech Lead 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.