Intuit machine learning engineer jobs
8 open Intuit machine learning engineer jobs, 8 first seen in the last 30 days, read from Intuit's own careers site. Most are in Mountain View, California.
- Open jobs
- 8
- First seen in the last 30 days
- 8
- Median days open, by our records
- 12
- Reposted
- None
What these jobs say
- Where
- Mountain View, California 8
- Level
- Senior 3, Staff 5
- Tools named most
- Python 8, AWS 7, Spark 7, SQL 5, Java 4, R 4, Scala 3, GCP 2
- Experience asked
- 8 years at least, at the median of 6 jobs that say
- Stated pay
- $228K median base, typically $194K to $263K, across 10 US postings with pay in the last year
Teams hiring and what the work is
- Machine learning engineering team
Build, deploy, and scale AI and ML models, owning the technical design and operational quality of your projects.
Senior Machine Learning Engineer - Fintech Risk AI/ML credit risk team (Team Apollo)
Build, code, and deploy ML models that detect and prevent credit risk across lending money movement products, working alongside data scientists and product engineers.
Senior Machine Learning Engineer, Credit Risk - Fintech Risk AI/ML Smart Money Services (SMS)
Build, deploy and maintain ML fraud and risk models at scale for Intuit's money movement events, with the web services that run them.
Senior Machine Learning Engineer, Smart Money Services - Fraud & Financial Risk - Consumer risk decisioning (consumer risk AI)
Own the data and platform layer for consumer risk models: feature pipelines, training and evaluation frameworks, and real-time inference serving feeding Intuit's decision engine under sub-second latency.
Staff Machine Learning Engineer, Consumer Risk AI
Open jobs
Counts cover every open machine learning engineer job we read from Intuit's own careers site, last checked Nov 14, 2026. The role is the one the work describes, whatever the title says. Ages use the day we first saw each job. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system. How we count Report an error