Senior Software Engineer - Machine Learning

Job description

### **Our Journey** The ShopBack Group is Asia-Pacific’s leading shopping, rewards, and payments platform, serving over 20 million active members across 13 markets. In 2025, the Group continued its global growth with its expansion into North America. Driven by the vision to make every day more rewarding, ShopBack is dedicated to saving members money and time, and delivering delight every day. The platform also enables merchants and brands to engage with their members in a cost-effective manner. Founded in 2014, ShopBack now powers over US$5.5 billion in annual sales for over 20,000 online and in-store partners, and has rewarded shoppers with more than US$900 million (over S$1 billion) in Cashback to date. Through its innovative offerings, ShopBack continues to create value for both members and merchants. Notably, its payment solution, ShopBack Pay, offers members a convenient and rewarding payment option at checkout. ### Your Adventure Ahead - Utilize Machine Learning: Enhance our products and improve the shopping experience for both users and merchants. This includes leveraging machine learning in areas such as recommendations, personalization, risk, fraud detection, search, and more. - Subject Matter Expertise: Be a subject matter expert in a specific ML domain while maintaining a solid understanding of product and user challenges. - Handle Ambiguity: Navigate and resolve ambiguous problem definitions effectively with or without dedicated Product Manager support. - Metrics Driven: Understand critical business and product metrics, apply the right tools and technologies, and drive efforts to positively influence those metrics. - Experimentation Culture: Foster a fast-paced, high-iteration experimental culture to test and refine solutions quickly. - Collaboration: Work effectively with cross-functional partners and stakeholders to set and achieve optimal outcomes. - Curious: Interest in exploring and learning the latest technologies in the industry. ### Essentials to Succeed - Significant prior success as a Machine Learning Engineer working on challenging problems at scale - 6+ years of industrial ML experience, with expertise in modeling and statistical modeling - Good understanding of data collection, aggregation, analysis, visualization, productionisation, and monitoring of ML products - aka MLOps - Ability to develop ML Products with good engineering practice and mindset - Strong desire to solve tough problems with scientific rigour at scale - An understanding of the value derived from getting results early and iterating - Education in a quantitative field such as Computer Science, Operations Research, Statistics, Econometrics or Mathematics - Strong skills in Python and machine learning and deep learning libraries (Pytorch and Tensorflow) - Passion to answer Product/Engineering questions with data - Demonstrated use of AI tools (e.g. ChatGPT, Cursor) to develop new or improve workflows, enhance productivity, and drive efficiency at scale.