Machine Learning Engineer

2 weeks ago

Singapore SHIELD Full time
Overview

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, Jakarta, Bengaluru, Beijing, and Singapore, we are rapidly achieving our mission - eliminating unfairness to enable trust for the world.

Responsibilities
  • 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 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
Seniority level
  • Associate
Employment type
  • Full-time
Job function
  • Engineering and Information Technology
Industries
  • Non-profit Organizations and Primary and Secondary Education
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