about 2 hours ago
Responsibilities
- Lead the architecture, design, and development of scalable data and ML infrastructure for fraud detection, risk evaluation, and trust systems.
- Build and optimize high-volume batch and real-time data pipelines with low latency and high reliability.
- Own end-to-end productionization of machine learning models, including deployment, scaling, performance, and operational requirements.
- Translate Data Science modeling requirements into scalable engineering solutions and bridge model development with production deployment.
- Define the long-term technical vision and roadmap for data processing, ML platform capabilities, and fraud detection infrastructure.
- Lead cross-functional initiatives, establish engineering best practices, and improve scalability, reliability, and operational excellence.
- Mentor senior engineers, drive technical decisions, and provide leadership during production incidents and architectural reviews.
Requirements
- 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 streaming technologies such as Apache Flink, Kafka, Spark Streaming, or similar frameworks.
- Strong proficiency in Java-based backend development and distributed-systems 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 experience in fraud detection, risk systems, trust and safety, payments risk, commerce, marketplace, fintech, or payments ecosystems.
- Preferred experience building ML platforms, model-serving infrastructure, feature stores, or inference pipelines.
- Preferred experience operating systems processing millions of events or transactions per day and partnering with Data Science teams to productionize models.
- Familiarity with GenAI tools for software development, debugging, testing, and engineering productivity is preferred.
- Experience with cloud-native architectures, containerized environments, and modern infrastructure platforms is preferred.
Benefits
- Hybrid, onsite, or remote work model; the standard hybrid model requires at least 3 days in the office and allows 2 days working from home, depending on role requirements.
- Employment-protection beneficiaries, including veterans and people with disabilities, may receive preferential treatment as required by applicable laws.
Tech Stack
About Coupang
Coupang is a technology and Fortune 150 company listed on the New York Stock Exchange (NYSE: CPNG) that provides retail, restaurant delivery, video streaming, and fintech services to customers around the world under brands that include Coupang, Eats, Play, Rocket Now, and Farfetch.