$185,000
median · per year, annualized USD
$163,800
median · per year, annualized USD
Senior/Staff Backend Engineer, Applied AI
Senior/Staff Full Stack Engineer, Applied AI
Senior Software Engineer, Machine Learning (Audio)
Research Engineer, Machine Learning (RL Velocity)
Research Engineer, Machine Learning (Reinforcement Learning)
Research Engineer, Machine Learning (Reinforcement Learning)
Research Engineer, Machine Learning (RL Velocity)
Software Engineer - AI
Machine Learning Engineer ($400k - $600k salary)
Senior Software Engineer, Machine Learning
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
| Company | Median | Roles |
|---|---|---|
Speechify
|
$170,000 | 144 |
Mindrift
|
$76,960 | 77 |
Booz Allen Hamilton
|
$162,000 | 76 |
OpenAI
|
$307,500 | 39 |
SpaceX
|
$145,000 | 35 |
General Motors
|
$203,125 | 34 |
Thomson Reuters
|
$204,200 | 30 |
CACI
|
$148,825 | 30 |
| Company | Median | Roles |
|---|---|---|
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 |
| Location | Median | Roles |
|---|---|---|
| San Francisco | $229,800 | 519 |
| New York | $212,500 | 483 |
| Seattle | $204,000 | 187 |
| Los Angeles | $203,625 | 64 |
| Boston | $196,000 | 137 |
| Singapore | $187,200 | 9 |
| Denver | $185,500 | 64 |
| Austin | $180,675 | 98 |
| Atlanta | $174,828 | 70 |
| London | $167,012 | 54 |
The median for AI Engineer is $185,000 per year (typically $145,000–$228,900), versus $163,800 for MLOps ($137,000–$193,500). That puts AI Engineer about 13% ahead at the median.
Both figures are computed live from active listings on JobsRadar and normalized to annualized USD, so AI Engineer and MLOps 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.