Machine Learning Engineer

• Design, build, and maintain production-grade ML solutions and infrastructure that power fraud detection
• Take AI & ML applications from prototype to production, partnering closely with data scientists and cross-functional teams
• Architect end-to-end ML infrastructure: feature engineering, data pipelines, model serving, CI/CD, observability, and retraining
• Lead development for ML systems with focus on performance, scalability, and maintainability
• Collaborate across teams (data scientists, data engineers, platform teams, business stakeholders) to align solutions with product needs
• Champion MLOps best practices: versioning, experimentation, testing, deployment, and monitoring of ML models
• Develop reusable components, templates, and automation to scale ML development
• Own features from concept to deployment and ensure seamless integration with platform components
• Participate in a shared on-call rotation

Senior Machine Learning Engineer

AI Engineer – Agent Evaluation Platform

Staff Data Engineer, AI