Machine Learning Engineer (Risk)

SHIELD, a leading device-first fraud intelligence platform, is seeking a Machine Learning Engineer to join their Risk team. The company is trusted by global unicorns like inDrive, Alibaba, Swiggy, Meesho, and TrueMoney, with offices spanning San Francisco, London, Berlin, Jakarta, Bengaluru, Beijing, and Singapore.

As a Machine Learning Engineer focusing on Risk, you'll be at the forefront of developing innovative ML solutions to combat fraud and ensure trust in digital businesses worldwide. You'll work with SHIELD AI to enhance the global standard for device identification (SHIELD Device ID) and actionable fraud intelligence.

Your role will involve designing and developing ML algorithms, analyzing large datasets, and discovering valuable insights that strengthen our fraud detection capabilities. You'll have the opportunity to work with various technologies and contribute to the entire machine learning lifecycle, from algorithm development to implementation.

The position requires strong technical skills in machine learning, databases, and programming languages like Python, C++, and C. You'll be working with both SQL and NoSQL databases, and your experience with data scaling will be crucial for optimizing system performance.

This is an excellent opportunity for someone passionate about applying ML to real-world problems, particularly in the cybersecurity and fraud prevention space. You'll be part of a global team working towards eliminating unfairness and enabling trust in the digital world. The role offers significant opportunities for growth and exploration of new technologies while making a meaningful impact on global digital security.