Machine Learning Engineer

Overview As a Machine Learning Engineer in Q2’s Risk & Fraud team, you will build production ML systems that detect fraud at scale, protecting trillions of dollars in transactions annually. You’ll collaborate with data scientists and engineers to turn models into real-time, reliable services and continuously improve their performance. This applied role emphasizes solving real customer problems with rigorously tested software. You’ll help shape next-generation fraud detection products and contribute to a mission-driven, collaborative culture. Compensation / Benefits Health & wellness benefits and competitive health insurance Hybrid work opportunities Flexible time off Career development & mentoring programs Parental leave for eligible new parents Community volunteering and philanthropy programs Responsibilities Research emerging fraud patterns and translate findings into new detection approaches Develop next-generation ML products across identity, behavior, and transaction fraud with customer input to shape product direction Build and optimize real-time, low-latency ML infrastructure for reliability, scalability, and performance Create and maintain data pipelines and systems for training, evaluation, and inference, productionalizing models Write clean, tested code following production engineering best practices and leveraging AI tooling Support monitoring and troubleshooting of production ML systems, including data pipelines and model performance Key requirements Bachelor’s degree in related field and 2+ years of relevant experience Proven experience in ML model development and deployment Strong knowledge of statistics, optimization, probability, and experimental methodologies Proficiency in Python, R, or Java Experience with ML frameworks/libraries (Tensor Flow, PyTorch, scikit-learn)Familiarity with cloud platforms and scalable computing resources Strong analytical, problem-solving, and collaboration skills Autonomy and ownership of team goals Empathy for end users and focus on customer value and technical quality Curiosity about latest ML developments and practical application Python, R, or Java Tensor Flow PyTorch