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.

Work arrangement
Yes