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 talented Machine Learning Engineer (Risk) who will join our team to develop innovative solutions that help us stay ahead of the curve. Responsibilities: • Develop machine learning models using Python and TensorFlow to identify fraudulent activity; • Collaborate with cross-functional teams, including data scientists, engineers, and product managers to design and implement new features; • Work closely with our risk team to integrate machine learning models into our fraud detection system; • Conduct experiments and analyze results to improve model performance; • Stay up-to-date with the latest advancements in machine learning and apply this knowledge to continuously improve our solutions. Requirements: • Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field; • 3+ years of experience in developing machine learning models using Python and TensorFlow; • Strong understanding of machine learning concepts, including supervised and unsupervised learning, regression, classification, clustering, etc. • Experience with data preprocessing, feature engineering, and model evaluation; • Familiarity with cloud-based technologies such as AWS or Google Cloud Platform; • Excellent problem-solving skills and attention to detail; • Strong communication and collaboration skills. What We Offer: • Competitive salary and benefits package; • Opportunity to work on cutting-edge projects that have a real impact; • Collaborative and dynamic work environment; • Professional development opportunities, including training and mentorship programs; • Flexible working hours and remote work options. If you are passionate about machine learning and want to join a team that is shaping the future of fraud detection, please apply with your resume and a brief cover letter explaining why you're the perfect fit for this role.