Mercury
Senior Machine Learning Operations Engineer
US, Canada
UTC-10 to UTC-3.5 $167k to $208k per year Full time
Senior
- Where you can live
- San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
- Working hours
- Overlap with UTC-10 to UTC-3.5
- Salary
- USD 166,600 to 208,300 per year
- Posted
- September 9, 2026
Python
TypeScript
React
Flask
FastAPI
SQL
Redis
Kafka
Snowflake
dbt
Airflow
Machine Learning
CI/CD
B2B SaaS
Summary from the posting
Mercury's use of machine learning in risk decisioning is growing fast in scope and in stakes. Models increasingly drive real-time decisions about fraud and financial crime, and the Machine Learning Platform (MLP) team exists to build a paved path from a trained model to a reliable production deployment, speeding up iteration, and ensuring granular production observability.
MLP owns the production ML lifecycle: the systems that take a model from registry through deployment, real-time inference, observability, and retraining. Our Data Science colleagues author and train the models.
This is a short summary. The full description, requirements and the application form are on Mercury's own career page.