Company Introduction
We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.
We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.
Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.
Role Overview:
Coupang’s Risk, Fraud & Trust Engineering organization is building next-generation platforms that protect the marketplace ecosystem through intelligent, scalable, and real-time decisioning systems. The team develops highly scalable fraud detection and risk evaluation platforms that process massive volumes of transactions, seller activities, and marketplace events while ensuring excellent customer and seller experiences.
As a Senior Staff Engineer, you will lead the architecture and development of large-scale ML-powered data platforms that bridge the gap between Data Science and Engineering. You will be responsible for building the infrastructure, real-time data pipelines, and serving systems required to deploy, scale, and operate machine learning models in production.
This role requires deep expertise in distributed systems, stream processing, data infrastructure, and ML model operationalization. You will partner closely with Data Scientists, Software Engineers, Product Managers, and business stakeholders to ensure fraud detection and risk models are efficiently deployed, highly performant, reliable, and capable of meeting strict business SLAs.
You will establish technical vision, drive architectural direction, and raise engineering standards across the organization while enabling the next generation of fraud prevention and trust platforms at Coupang scale.
Key Responsibilities:
- Lead the architecture, design, and development of scalable data and ML infrastructure supporting fraud detection, risk evaluation, and trust systems.
- Build and optimize large-scale batch and real-time data pipelines capable of processing high-volume events with low latency and high reliability.
- Own the end-to-end productionization of machine learning models, ensuring deployment architectures meet performance, scalability, and operational requirements.
- Partner closely with Data Scientists and Engineering teams to bridge model development and production deployment, translating complex modeling requirements into scalable engineering solutions.
- Define long-term technical vision and roadmap for data processing, ML platform capabilities, and fraud detection infrastructure.
- Lead complex cross-functional initiatives, establish engineering best practices, and raise the bar for system scalability, reliability, and operational excellence.
- Mentor senior engineers, drive technical decision-making, and provide leadership during critical production incidents and architectural reviews.
Basic Qualifications
- 13+ years of experience in backend engineering, data engineering, or large-scale distributed systems development
- Strong experience building large-scale, real-time distributed data processing systems
- Hands-on experience with data streaming technologies such as Apache Flink, Kafka, Spark Streaming, or similar frameworks
- Strong proficiency in Java-based backend development and distributed system architecture
- Experience designing and building low-latency, high-throughput data pipelines and serving systems
- Experience deploying, scaling, and optimizing machine learning models in production environments
- Strong knowledge of system design, scalability, fault tolerance, and operational excellence
Preferred Qualifications
- Experience in fraud detection, risk systems, trust & safety, payments risk, or similar domains
- Familiarity with commerce, marketplace, fintech, or payments ecosystems
- Experience building ML platforms, model-serving infrastructure, feature stores, or inference pipelines
- Experience operating systems that process millions of events or transactions per day
- Experience partnering closely with Data Science teams to productionize machine learning models
- Familiarity with leveraging GenAI tools for software development, debugging, testing, and engineering productivity
- Experience working with cloud-native architectures, containerized environments, and modern infrastructure platforms
Type of work model
- Hybrid / Onsite / Remote working
Our Hybrid work model: Coupang hybrid work model is designed to enable a culture of collaboration that acts a catalyst to enrich the experience of employees. Employees are required to work at least 3 days in the office per week, with the flexibility to work from home 2 days a week, depending on the role requirement. Some businesses may require more time in office due to nature of work.
Details to consider
- Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.
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