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$192,050–$254,750.
Based on 240 similar postings.
Employer
About Q2
Q2 Holdings is a cloud-based banking software company providing digital banking solutions to banks, credit unions, and alternative financial companies, including consumer and business banking platforms. Industry: Financial Technology & Digital Banking
As a Machine Learning Engineer on the Risk & Fraud team, you will build and operate production systems designed to detect fraud at scale. You will collaborate with data scientists to transform models into reliable, real-time systems while researching emerging fraud patterns to develop new detection approaches across identity, behavior, and transaction categories. Your daily work involves building and optimizing low-latency infrastructure, maintaining pipelines for training and inference, and writing well-tested code using production engineering best practices. You will utilize Python, R, or Java alongside frameworks like TensorFlow, PyTorch, and scikit-learn to solve complex problems in the financial services domain. The role focuses on creating scalable applications that protect transactions from fraud while ensuring high performance and reliability within a sophisticated risk management environment for financial institutions.
What does a Machine Learning Engineer earn?
Median $236000 from 319 postings across 54 companies.