MLE 4 (Fraud)

Roles and Responsibilities-

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• Develop, maintain, and own key fraudulent CV models, which shapes the whole fraud product offering.
• Design and implement machine learning, deep learning, classical CV focused on fraud detection.
• Research to support the deployment of the advanced algorithms.
• Deploy models as AWS SageMaker endpoints or directly onto devices.
• Stay updated with the latest advancements in machine learning, deep learning, and computer vision by engaging with academic papers and attending industry conferences.
• Work collaboratively with other engineers and product managers in an Agile development environment.Experience and Qualifications
• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
• A minimum of 6+ years of commercial experience in the field of machine learning/deep learning, not including time spent studying (2 years with Master’s).
• Must have: experience with training of DL models for deepfakes, synthetic data, or gen AI data detection.
• Deep understanding of how to convert ML metrics to product goals.
• Hands-on experience with PyTorch and in developing production-grade Python code.
• Demonstrated experience in implementing best practices for monitoring and maintaining ML models in production environments.
• Strong communication and problem-solving skills.