Machine Learning Engineer

As a Machine Learning Engineer at Q2, you will help build and operate production systems that power our fraud products, bringing models into production in a reliable, scalable, and maintainable way. You will work closely with data scientists and engineers to support the entire ML lifecycle, from training and evaluation to deployment and ongoing monitoring.

• Build and maintain systems and pipelines that support training, evaluation, and inference for machine learning models.
• Contribute to deploying machine learning models into production environments and ensuring they run reliably at scale.
• Write clean, maintainable, and well‑tested code following production engineering best practices.
• Support monitoring and troubleshooting production ML systems, including data pipelines and model performance.
• Collaborate with data scientists and engineers to productionalize models and integrate them into scalable applications.
• Help improve the reliability, scalability, and performance of ML systems over time.
• Contribute to improving tooling and infrastructure that supports the ML development lifecycle.

• Bachelor’s degree in a relevant field and a minimum of 2+ years of related experience; or an advanced degree; or equivalent related work experience.
• Proficiency in Python.
• Experience writing clean, maintainable code and using version control (e.g., Git).
• Experience with machine learning and common frameworks (e.g., PyTorch, Tensor Flow, scikit‑learn).
• Fluent written and oral communication in English.
• Authorized to work for any employer in the U.S.; no visa sponsorship is available.

• Experience building end‑to‑end ML systems, including data pipelines, model training, deployment, and monitoring.
• Experience deploying or integrating machine learning models into applications.
• Experience building APIs, backend services, or working with distributed systems.
• Familiarity with cloud platforms (AWS, GCP, or Azure).
• Exposure to MLOps concepts such as CI/CD and model monitoring.
• Experience working with large datasets or data processing frameworks.
• Experience with other programming languages (e.g., Typescript).

• Health & Wellness benefits, including competitive health insurance and generous paid parental leave.
• Hybrid work opportunities and flexible time off.
• Career development & mentoring programs.
• Community volunteering & company philanthropy programs.
• Employee peer recognition programs.

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.