SHIELD is a device-first risk intelligence company. We are dedicated to helping organizations worldwide eliminate fake accounts and all malicious activity. Leveraging AI, we identify the root of fraud with the SHIELD Device ID and provide actionable risk intelligence in real time, helping all online businesses stop fraud, build trust, and drive growth. With offices in San Francisco, Miami, London, Berlin, Jakarta, Bengaluru, Beijing, and Singapore, we are rapidly achieving our mission - eliminating unfairness to enable trust for the world.

Responsibilities

As a Senior Machine Learning Engineer (Risk), you will develop and leverage innovative machine learning solutions to solve complex sets of problems and applications. By analyzing and detecting patterns in vast amounts of data, you will have a good understanding of machine learning life cycle-algorithms, data structures and design patterns. We are looking for talented and passionate individuals who are proactive in identifying problems and have the logical thought process and skills to solve them. There will be many opportunities to explore new tech stacks and to work on advanced technologies.

• Ability to design and develop machine learning algorithms
• Discover, design, and develop analytical methods to support novel approaches of data and information processing
• Identify and apply appropriate methods to process and analyze large data-sets of labelled and unlabeled records, and discover new valuable insights for the system
• Provide support on other part of the system (not limited to Machine Learning)
• Conduct software performance analysis, scaling, tuning and optimization
• Review and contribute to improve current software and system architecture for stability and to optimize performance
• Research & development of fraud detection solution

Requirements

• Minimum 5 years of relevant experience
• Minimum Bachelor Degree in Computer Science, Information System with Machine Learning specialization or equivalent
• Strong foundation in database and data scaling
• Experience with various Machine Learning algorithms and ability to apply in real life cases
• Experience in MySQL, NoSQL and Columnar database
• Experience in C++, C, Python and other programming languages will be an advantage
• Prior experience in e-payments or e-commerce industry is a plus
• Strong analytical, interpersonal, communication and presentation skills