2027 Summer Internship - Machine Learning Engineer

Q2 India

Austin (TX)

On-site

USD 26,000 - 42,000

Full time

4 days ago
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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

As passionate about our people as we are about our mission.

Why Join Q2?

Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, alternative finance companies, and fintechs in the U.S. and internationally. Our mission is simple: build strong and diverse communities through innovative financial technology—and we do that by empowering our people to help create success for our customers.

What Makes Q2 Special?

Being as passionate about our people as we are about our mission. We celebrate our employees in many ways through our year-round Q2 ChangeMakers awards program and global moments of recognition and connection.

We invest in the growth and development of our team members through ongoing learning opportunities, internal mobility, and meaningful leadership relationships.

We also know that nothing builds trust and collaboration like having fun and giving back together. From company-wide volunteer days to events like our Q2 Homecoming Week—featuring learning, community service, and culture-building experiences—we create opportunities to connect, grow, and make an impact.

Projects You Could Work On

You’ll get exposure across the full lifecycle of applied ML — from model development and evaluation to deployment, monitoring, and improvement — on software that solves real problems for real customers.

Recent intern projects on this team and others have included enhancing our Iso Framework, building data pipelines for operational insights, and researching new approaches to emerging problems.

What You’ll Do
  • Support research into emerging fraud and abuse patterns, and help translate findings into new detection ideas
  • Help build and test features for ML products across identity, behavior, and transaction fraud
  • Assist in building and maintaining pipelines that support training, evaluation, and inference of ML models
  • Write clean, well-tested code alongside engineers, using modern AI-assisted development tools
  • Help monitor and troubleshoot production ML systems, including data pipelines and model performance
What You’ll Bring
  • Currently pursuing a degree in Computer Science, Data Science, Machine Learning, or a related field
  • Coursework or project experience with Python (R or Java a plus)
  • Exposure to ML frameworks or libraries such as TensorFlow, PyTorch, or scikit-learn
  • Foundational knowledge of statistics, probability, or experimental methods
  • Strong analytical thinking, curiosity, and a collaborative mindset
  • Nice to Have
  • Coursework or personal projects involving fraud detection, risk modeling, or similar domains
  • Exposure to APIs, backend services, or working with large datasets
  • Comfort using AI-assisted development tools (e.g., Claude Code)

This position requires fluent written and oral communication in English.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Our Culture & Commitment

We’re proud to foster a supportive, inclusive environment where career growth, collaboration, and wellness are prioritized.

  • Our benefits go beyond healthcare—offering resources for physical, mental, and professional well-being.
  • Q2 employees are encouraged to give back through volunteer work and nonprofit support through our Spark Program (see more).

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, or veteran status.

Applicants in California or Washington State may not be exempt from federal and state overtime requirements.

Mission

Q2’s mission is build strong and diverse communities by strengthening their financial institutions. That mission shapes the technology we build, how we serve our customers, and how we show up for each other.

Vision

We started with a straightforward belief: technology could fundamentally change how financial institutions serve their communities. More than 20 years later, that belief still drives us. Q2 delivers digital banking and lending solutions that help financial institutions deepen relationships, improve experiences, and grow. Across every department and region, Q2 team members bring creativity, collaboration, and purpose to building technology that makes banking stronger, easier, and more human.

Culture & Values

Q2’s culture is built by Q2ers and grounded in ten guiding principles that define how we show up for each other, our customers, and our communities. We take our mission seriously. We also have fun doing it. Teams across the company work together to solve hard problems, move quickly, and make a real impact on the financial institutions and communities we serve.

We’re also helping shape how AI is applied in financial services, bringing the same disciplined, banking‑first approach Q2 has practiced for more than 20 years to this next chapter of innovation.

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