Senior Machine Learning Engineer - Fraud (Research Scientist)

This role involves leading applied research to develop advanced fraud detection models using cutting-edge machine learning techniques across various data modalities, with a focus on translating research into scalable production systems.

• Lead research on fraud detection models
• Prototype state-of-the-art architectures
• Collaborate with engineering teams
• Publish research findings
• Translate research into production

The environment includes large-scale data processing, graph neural networks, transformer models, and multimodal learning, primarily using Python for prototyping and experimentation.

The ideal candidate is a senior research scientist with a PhD and 3+ years of experience in machine learning research, specializing in fraud detection, graph neural networks, and multimodal learning. They have a strong publication record and proficiency in Python.