Senior Machine Learning Engineer (Risk)

SHIELD is a device-first fraud intelligence platform that helps digital businesses worldwide eliminate fake accounts and stop all fraudulent activity. Powered by SHIELD AI, we identify the root of fraud with the global standard for device identification (SHIELD Device ID) and actionable fraud intelligence, empowering businesses to stay ahead of new and unknown fraud threats. We are trusted by global unicorns like inDrive, Alibaba, Swiggy, Meesho, TrueMoney, and more. With offices in LA, London, We are looking for a highly skilled Senior Machine Learning Engineer (Risk) who will be responsible for developing and maintaining our risk-based fraud detection models using machine learning algorithms. The ideal candidate should have experience with deep learning frameworks such as TensorFlow or PyTorch, and proficiency in programming languages like Python or R. Responsibilities: • Develop and maintain risk-based fraud detection models using machine learning algorithms, • Collaborate with cross-functional teams to integrate new features and improve existing ones, • Design and implement experiments to evaluate the performance of our models, • Work closely with data scientists to develop and refine predictive models, • Stay up-to-date with the latest advancements in machine learning and apply them to our risk-based fraud detection models. Requirements: • Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, • At least 3 years of experience in developing and maintaining machine learning models, • Strong understanding of deep learning frameworks such as TensorFlow or PyTorch, • Proficiency in programming languages like Python or R, • Experience with data preprocessing and feature engineering, • Excellent problem-solving skills and attention to detail. What We Offer: • Competitive salary and benefits package, • Opportunity to work on cutting-edge machine learning projects, • Collaborative and dynamic work environment, • Professional development opportunities, • Flexible working hours and remote work options.