$187,500
median · per year, annualized USD
$200,000
median · per year, annualized USD
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
Lead Safety Engineer, Robotics
Firmware Engineer, Robotics
Machine Learning Engineer, Distributed Data Systems - Robotics
Software Engineer, Distributed Data Systems - Robotics
Inference Engineer, Robotics
Electrical Engineer, Robotics
Staff Robotics Engineer / Tech Lead – Whole-Body Control & Robot Learning
Software Engineer: Robotics Controls
Software Engineer: ML Robotics Systems
Staff Robotics Software Engineer, Air Vehicle Autonomy
| Company | Median | Roles |
|---|---|---|
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 |
| Company | Median | Roles |
|---|---|---|
Anduril Industries
|
$222,000 | 53 |
Field Ai
|
$185,000 | 9 |
OpenAI
|
$370,000 | 7 |
| SA Skild AI | $200,000 | 7 |
Neuralink
|
$155,750 | 6 |
DoorDash USA
|
$207,500 | 5 |
Intrinsic
|
$174,050 | 5 |
Agility Robotics
|
$215,750 | 4 |
| Location | Median | Roles |
|---|---|---|
| Boston | $222,000 | 13 |
| New York | $214,750 | 4 |
| Seattle | $214,750 | 6 |
| Austin | $212,000 | 9 |
| San Francisco | $206,000 | 36 |
| Denver | $150,000 | 3 |
| Los Angeles | $131,250 | 6 |
The median for MLOps is $187,500 per year (typically $147,500–$236,325), versus $200,000 for Robotics ($170,000–$222,000). That puts Robotics about 7% ahead at the median.
Both figures are computed live from active listings on JobsRadar and normalized to annualized USD, so MLOps and Robotics are compared on equal terms regardless of the currency each role was originally posted in. Only roles that publish a salary range feed the medians; numbers refresh every few hours as new roles post and older ones close, so this comparison reflects the market right now rather than a fixed survey. Use it as a directional benchmark when weighing one path against the other.