Senior Machine Learning Engineer
SHIELD is a mobile-first risk intelligence company that helps world-leading enterprises build trust and safety by stopping fraud and abuse. Trusted across all continents by superapps, top e-commerce platforms and e-wallets, we protect over 7 billion devices and 500 million user accounts every year. Headquartered in Singapore, we have offices in Germany, United States, Indonesia, and China.
As a Senior Machine Learning Engineer, you will be responsible for the research and development of ML models and algorithms, enhancing our cyber fraud and identity solutions. This role requires a broad and in-depth knowledge of machine learning and the software engineering expertise to develop and deploy highly scalable algorithms that will have direct impact on SHIELD’s core services to our clients. The ideal candidate should be a keen problem solver and a hands-on team player who is passionate about helping businesses stop fraud and abuse.
- Improve existing models and algorithms responsible for identifying sophisticated fraud patterns, trends and emerging threats
- Build new features and enhance our risk engine
- Research and develop ways to automate and scale our real-time fraud detection mechanisms
- Work closely with our infrastructure, risk and product teams to deliver risk intelligence at scale with SHIELD’s tech stack
- Minimum 5 to 10 years of 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
- Able to work in a fast-paced environment
Be part of the powerful team behind SHIELD’s powerful technology. Send your resume to [email protected] now!