2027 Summer Internship - Machine Learning Engineer

Q2 Software • Austin, TX

1d

About The Position

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. 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.

Requirements

• 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
• Fluent written and oral communication in English
• Authorized to work for any employer in the U.S.

Nice To Haves

• 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)

Responsibilities

• 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

Benefits

• Resources for physical, mental, and professional well-being
• Volunteer work and nonprofit support through our Spark Program

What This Job Offers

• Career Level: Intern
• Education Level: No Education Listed