Staff Machine Learning Engineer R&D, Fraud Intelligence

Working at the intersection of applied research and large-scale engineering, you'll develop novel approaches in anomaly detection, supervised learning, and continual learning to uncover and adapt to evolving fraud patterns. Assist in the development and optimization of machine learning models. Preprocess and analyze datasets to ensure data quality. Collaborate with senior engineers and data scientists on model deployment. Conduct experiments and run machine learning tests. Stay updated with the latest advancements in machine learning. Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience. Familiarity with ML frameworks like TensorFlow or scikit-learn. Strong analytical and problem-solving skills.