Machine Learning Engineer Internship

Q2

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Austin, TX
Employment
Intern
Posted
6 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $201k
$132k most similar roles pay here $280k

This listing doesn't post a salary. Most similar roles pay $146,500–$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

Q2 currently has 35 open roles on FindRole.

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At a glance

TL;DR · Machine Learning Engineer Internship

The 2027 Summer Internship - Machine Learning Engineer role involves working on a team focused on the full lifecycle of applied machine learning, including model development, evaluation, deployment, monitoring, and improvement. The intern will support research into emerging fraud and abuse patterns, translate findings into detection ideas, build features for identity and transaction fraud products, and maintain pipelines for training and inference. Day-to-day tasks include writing clean, well-tested code using AI-assisted tools and troubleshooting production systems. Required skills include proficiency in Python, with R or Java as a plus, along with experience in frameworks like TensorFlow, PyTorch, or scikit-learn. Candidates should possess foundational knowledge of statistics and probability while working on software that addresses fraud detection and risk modeling within the financial services domain to solve real problems for customers.

What does a Machine Learning Engineer earn?

Median $236631 from 328 postings across 54 companies.

See salary data

What you'll do

  • Research emerging fraud and abuse patterns to develop new detection ideas.
  • Build and test features for ML products across identity, behavior, and transaction fraud.
  • Develop and maintain pipelines that support the training, evaluation, and inference of ML models.
  • Write clean, well-tested code using modern AI-assisted development tools.
  • Monitor and troubleshoot production ML systems and data pipelines.
  • Evaluate model performance to ensure high-quality software for customers.

What we're looking for

  • Currently pursuing a degree in Computer Science, Data Science, Machine Learning, or a related field.
  • Experience with Python (R or Java is a plus).
  • Exposure to ML frameworks or libraries such as TensorFlow, PyTorch, or scikit-learn.
  • Foundational knowledge of statistics, probability, or experimental methods.
  • Fluent written and oral communication in English.
  • Authorization to work for any employer in the U.S.
  • Coursework or personal projects involving fraud detection, risk modeling, or similar domains (preferred).
  • Exposure to APIs, backend services, or working with large datasets (preferred).

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