Innovative Machine Learning Engineer for Fraud Prevention Systems

Drive impactful fraud prevention as a Machine Learning Engineer. Develop intelligent systems to protect customers while enhancing user experience with seamless transaction assessments. This role focuses on building feature engineering pipelines and optimizing production models. You'll craft scalable, reliable solutions and ensure smooth integration with diverse machine learning frameworks. Collaborate with a team committed to technical excellence, and feedback-driven improvements in design and architecture. Key Responsibilities: • Design and maintain machine learning models for risk assessment • Build scalable feature engineering pipelines for real-time data • Optimize model performance through MLOps best practices • Participate in code and design reviews for system enhancements • Collaborate on architectural discussions to improve team practices Requirements: • Degree in computer science, data science, or related field • 2+ years experience with machine learning systems development • Proficiency in Python, Go, or Scala • Hands-on with ML frameworks like PyTorch or scikit-learn • Familiarity with cloud platforms such as AWS or Azure Leverage your skills in machine learning to create efficient systems that enhance customer trust and operational reliability.