Machine Learning Engineer
3 weeks ago
SHIELD is a cutting-edge fraud intelligence platform that empowers digital businesses to combat fake accounts and stop fraudulent activity worldwide.
Our platform, powered by SHIELD AI, leverages the global standard for device identification (SHIELD Device ID) and actionable fraud intelligence to help businesses stay ahead of new and unknown fraud threats.
We are trusted by leading global companies like inDrive, Alibaba, Swiggy, Meesho, TrueMoney, and more. With offices in San Francisco, London, Berlin, Jakarta, Bengaluru, Beijing, and Singapore, we are rapidly achieving our mission - eliminating unfairness to enable trust for the world.
Job Responsibilities
As a Machine Learning Engineer (Risk), you will develop and leverage innovative machine learning solutions to solve complex 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 Software Engineers 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.
- 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 datasets of labelled and unlabeled records, and discover new valuable insights for the system
- Provide support on other parts 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 solutions
Requirements
- Minimum 5 years of experience
- Minimum 1 year of experience in Unsupervised Model
- 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
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