Machine Learning Engineer (Risk)

SHIELD is at the forefront of fraud prevention technology, offering a device-first fraud intelligence platform that protects digital businesses worldwide. As a Machine Learning Engineer (Risk), you'll be integral to developing cutting-edge ML solutions for fraud detection and prevention. The role combines deep technical expertise in machine learning with practical application in fraud prevention.

You'll work with large datasets, developing and implementing ML algorithms to detect patterns and prevent fraudulent activities. The position offers exposure to various aspects of the ML lifecycle, from algorithm design to production deployment. SHIELD's global presence, with offices in LA, London, Jakarta, Bengaluru, Beijing, and Singapore, provides a truly international working environment.

The company serves major unicorns like inDrive, Alibaba, Swiggy, Meesho, and TrueMoney, offering you the opportunity to work on solutions that impact millions of users. You'll be part of a team that's passionate about using AI to create a more trustworthy digital ecosystem. The role requires strong technical skills in machine learning, databases, and programming languages like Python, C++, and C.

This position is perfect for someone who wants to apply their ML expertise to real-world fraud prevention challenges while working with a diverse, global team. You'll have the opportunity to contribute to the entire ML pipeline, from research to implementation, while helping shape the future of digital trust and security.