ML Engineer Intern — Fraud Detection & ML Pipelines

Q2 India; Austin (TX); On-site; USD 26,000 - 42,000; Full time

Job summary

Q2 is seeking a curious ML intern in Austin, TX to work on applied analytics and fraud-detection projects. You will join a team shipping ML-powered features across identity, behavior, and transactions, from data pipelines to model evaluation.

Ideal candidates are pursuing CS/Data Science/ML degrees and have Python experience; exposure to TensorFlow, PyTorch, or scikit-learn is a plus. Good communication and collaboration are essential.

Qualifications

• Current student pursuing CS, DS, ML or related field.
• Python experience through coursework or projects.
• Familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Strong analytical thinking and collaboration.

Responsibilities

• Support research into emerging fraud and abuse patterns.
• Build and test ML features across identity, behavior, and transactions.
• Help maintain data pipelines for training and inference.
• Write clean, tested code with engineers and monitor production ML systems.

Skills

Python

ML frameworks

Statistics

Education

Pursuing CS/DS/ML degree

Tools

TensorFlow

PyTorch

scikit-learn

Job description

Q2 is seeking a curious ML intern in Austin, TX to work on applied analytics and fraud-detection projects. You will join a team shipping ML-powered features across identity, behavior, and transactions, from data pipelines to model evaluation.

Ideal candidates are pursuing CS/Data Science/ML degrees and have Python experience; exposure to TensorFlow, PyTorch, or scikit-learn is a plus. Good communication and collaboration are essential.