Real-Time Fraud ML Engineer (Hybrid)
q2Charlotte (NC)
About the role
Q2, a leading provider of digital banking and lending solutions, is seeking a Machine Learning Engineer to build production fraud-detection systems at scale. You will collaborate with data scientists to turn models into reliable real-time applications.
This role offers hands-on exposure across model development, evaluation, deployment, and monitoring, with opportunities to impact fraud losses for financial institutions and their customers.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
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