$200,000
mediana · por ano, anualizado em USD
$164,400
mediana · por ano, anualizado em USD
Senior Software Engineer, Machine Learning (Audio)
Research Engineer, Machine Learning (Reinforcement Learning)
Research Engineer, Machine Learning (RL Velocity)
Research Engineer, Machine Learning (Reinforcement Learning)
Research Engineer, Machine Learning (RL Velocity)
Machine Learning Engineer ($400k - $600k salary)
Senior Software Engineer, Machine Learning
Machine Learning Engineer, Monetization AI/ML
Staff Backline Engineer – ML/AI
Machine Learning Engineer, Implicit Signals
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
Lead Software Platform Engineer, MLOps
Staff MLOps Engineer
Software Engineer - ML Ops (R37)
Senior Staff ML Ops Engineer
Matterport - Senior ML Ops Engineer
| Empresa | Mediana | Funções |
|---|---|---|
General Motors
|
$205,400 | 29 |
Booz Allen Hamilton
|
$162,000 | 27 |
CACI
|
$152,650 | 20 |
Reddit
|
$276,000 | 17 |
Pinterest
|
$246,638 | 17 |
Nuro
|
$242,540 | 16 |
DoorDash USA
|
$251,400 | 15 |
Torc Robotics
|
$195,050 | 15 |
| 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 |
|---|---|---|
| Los Angeles | $256,200 | 26 |
| Singapore | $244,400 | 4 |
| San Francisco | $237,500 | 199 |
| New York | $220,000 | 146 |
| Seattle | $219,000 | 70 |
| Boston | $215,050 | 35 |
| London | $207,031 | 16 |
| Austin | $203,000 | 33 |
| Denver | $194,100 | 19 |
| Atlanta | $189,038 | 12 |
A mediana para ML Engineer é $200,000 por ano (normalmente $158,250–$243,325), contra $164,400 para MLOps ($137,750–$194,125). Isso coloca ML Engineer cerca de 22% à frente na mediana.
Ambos os números são calculados ao vivo a partir de vagas ativas na JobsRadar e normalizados para USD anualizado, então ML 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.