Machine Learning Engineer Intern

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Q2

1,001-5,000 employeesAustin, TXFinancial Services
Actively hiringPaidSummer 2027Financial Services
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Best applied by Dec 28

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About the role#

Q2 is looking for a Machine Learning Engineer Intern for the Summer 2027 term. You will work on the full lifecycle of applied machine learning, from model development and evaluation to deployment and monitoring. This role is based on-site in Cary, North Carolina.

What you'll do#

  • Research emerging fraud and abuse patterns and help turn those findings into new detection ideas.
  • Build and test features for machine learning products focused on identity, behavior, and transaction fraud.
  • Assist in building and maintaining pipelines that support model training, evaluation, and inference.
  • Write clean, well-tested code.
  • Monitor and troubleshoot production machine learning systems, including data pipelines and model performance.

What you'll need#

  • Current enrollment in a degree program for Computer Science, Data Science, Machine Learning, or a related field.
  • Coursework or project experience using Python.
  • Exposure to machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Foundational knowledge of statistics, probability, or experimental methods.
  • Strong analytical thinking, curiosity, and a collaborative mindset.
  • Fluent written and oral communication in English.

Location & details#

  • Location: Cary, North Carolina (On-site).
  • Term: Summer 2027.
  • Employment: Full-time, paid internship.
  • Note: This position does not offer visa sponsorship.

About Q2

Q2 provides digital banking and lending technology for banks, credit unions, and fintech firms. The company builds software for consumer, small business, and corporate account holders. Based in Austin, Texas, it operates internationally with a workforce of 1,001 to 5,000 employees. It focuses on security and data-driven financial experiences.

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