$160,000
mediana · por ano, anualizado em USD
$164,400
mediana · por ano, anualizado em USD
Pre-training Data Infrastructure Engineer
Staff+ Research Engineer, RL Data Platform
Staff / Principal Data Engineer
Software Engineer - Data Aquisition (systems)
Software Engineer, Data Acquisition
Research Engineer - Environments, Data and Post-Training
Software Engineer, Frontier Data Products
Data Engineer
Software Engineer, Search Systems - Code Data
Software Engineer, Frontier Data Products
Staff Machine Learning Operations Engineer
Machine Learning Engineer/Senior Machine Learning Engineer - Devops, AI for Drug Discovery
Principal Machine Learning Operations Engineer
Lead ML Engineer - Advance AI (applied ML, LLM's, ML Ops)
Senior / Staff ML Ops Engineer
Staff MLOps Engineer
Lead Software Platform Engineer, MLOps
Software Engineer - ML Ops (R37)
Senior Staff ML Ops Engineer
Matterport - Senior ML Ops Engineer
| Empresa | Mediana | Funções |
|---|---|---|
Booz Allen Hamilton
|
$126,800 | 81 |
Accenture Federal Services
|
$149,800 | 28 |
CACI
|
$139,950 | 25 |
Olsson
|
$120,000 | 21 |
Leidos
|
$151,475 | 19 |
Northrop Grumman
|
$127,350 | 18 |
Blue Origin
|
$188,162 | 17 |
Anduril Industries
|
$193,000 | 16 |
| Empresa | Mediana | Funções |
|---|---|---|
Weekday AI
|
$202,800 | 2 |
Target
|
$197,000 | 2 |
Workday
|
$150,400 | 2 |
RELX
|
$140,450 | 2 |
Booz Allen Hamilton
|
$126,300 | 2 |
Shirley Ryan AbilityLab
|
$88,225 | 2 |
Garner Health
|
$324,500 | 1 |
AiDASH, Inc.
|
$250,000 | 1 |
| Local | Mediana | Funções |
|---|---|---|
| San Francisco | $211,000 | 192 |
| Seattle | $196,700 | 69 |
| New York | $192,736 | 213 |
| Los Angeles | $180,350 | 33 |
| Boston | $173,750 | 53 |
| Singapore | $165,000 | 5 |
| Austin | $161,450 | 51 |
| Chicago | $154,600 | 90 |
| Denver | $153,300 | 56 |
| Atlanta | $153,300 | 35 |
A mediana para Data Engineer é $160,000 por ano (normalmente $127,488–$198,000), contra $164,400 para MLOps ($137,250–$195,375). Isso coloca MLOps cerca de 3% à frente na mediana.
Ambos os números são calculados ao vivo a partir de vagas ativas na JobsRadar e normalizados para USD anualizado, então Data Engineer e MLOps são comparados em igualdade de condições, independentemente da moeda em que cada vaga foi originalmente publicada. Apenas as vagas que publicam uma faixa salarial alimentam as medianas; os números são atualizados a cada poucas horas conforme novas vagas são publicadas e as antigas são encerradas, então esta comparação reflete o mercado agora, e não uma pesquisa fixa. Use-a como referência direcional ao pesar um caminho contra o outro.