$214,750
median · per year, annualized USD
$187,500
median · per year, annualized USD
Associate Counsel, Corporate
Legal Counsel (corporate / commercial, 3-5 PQE), hybrid/remote
Director, Corporate Counsel
Legal Counsel
General Counsel
REIT Special Counsel / Senior Associate
Real Estate Associate / Special Counsel (Lender-Side Focus)
Antitrust and Competition Associate / Special Counsel
Real Estate Senior Associate / Special Counsel ("Dirt" Focus)
Estate & Tax Planning Legal Counsel
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
| Company | Median | Roles |
|---|---|---|
| TM Tyson & Mendes LLP | $175,000 | 39 |
Fivetran
|
$214,096 | 25 |
Axiom Talent Platform
|
$214,750 | 22 |
Alliance Defending Freedom
|
$159,583 | 12 |
Barnes & Thornburg LLP
|
$275,000 | 10 |
Crusoe
|
$235,000 | 9 |
Clearway Energy
|
$215,000 | 9 |
Harvey
|
$237,500 | 8 |
| 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 |
| Location | Median | Roles |
|---|---|---|
| San Francisco | $226,125 | 122 |
| New York | $221,000 | 164 |
| Seattle | $220,000 | 24 |
| Boston | $219,875 | 12 |
| Los Angeles | $214,750 | 28 |
| Atlanta | $214,750 | 11 |
| Denver | $214,096 | 49 |
| Chicago | $214,050 | 19 |
| Dublin | $204,500 | 3 |
| Austin | $193,870 | 14 |
The median for Counsel is $214,750 per year (typically $180,000–$250,000), versus $187,500 for MLOps ($147,500–$236,325). That puts Counsel about 15% ahead at the median.
Both figures are computed live from active listings on JobsRadar and normalized to annualized USD, so Counsel 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.