Senior Software Engineer, Machine Learning, Payments - Singapore

Product area

Whether it is paying online with Autofill, using tap and pay in stores, or using the Google Pay app, the Payments team at Google is focused on making payments simple, seamless, and secure. In addition to consumer payment technologies, the Payments team also powers the money movement between Google and its consumers and businesses.

Job description

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

Qualifications

Job responsibilities

• Develop effective machine learning models and optimization solutions for identifying the best credit products for Google Pay users.
• Reduce infrastructure complexity, improve reliability, and ensure security and privacy compliance.
• Design and build infrastructure for training and serving ML models in a secure and privacy-compliant manner.
• Analyze data for statistical insights, design experiments and metrics, and generate ideas for improvement.

Minimum qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages (e.g., Java, C/C++, Python, JavaScript, or Go).
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 3 years of experience building data pipelines for machine learning.

Preferred qualifications

• Master's degree or PhD in Computer Science, or a related technical field.
• Experience in developing and maintaining machine learning models in production.
• Experience in analyzing and improving efficiency, scalability, and stability of various systems.
• Experience with sandboxing solutions, ensuring the highest standards of security and privacy.