12 hours ago
Taipei, TaiwanStaff+
Responsibilities
- Collaborate with Data Scientists and Data Analysts to convert experimental code into production-ready architectures through refactoring, model hosting, and integration.
- Design and formalize end-to-end model deployment, versioning, and reproducibility workflows.
- Build and maintain scalable data pipelines using distributed data-processing ecosystems.
- Standardize Data Science development environments and establish foundational ML infrastructure, feature-store integration, and data-versioning practices.
- Develop and operationalize predictive solutions using statistical, analytical, or heuristic approaches.
- Monitor, maintain, and optimize deployed solutions while addressing bottlenecks, technical debt, and production availability.
Requirements
- Bachelor’s or master’s degree in computer science, software engineering, industrial engineering, or another quantitative discipline.
- 5+ years of relevant industry software or ML engineering experience.
- Hands-on MLOps and model-deployment lifecycle experience, including code refactoring, Docker, Kubernetes, and model-hosting strategies such as FastAPI, REST APIs, or cloud-native endpoints.
- Proficiency in Python, SQL, and distributed data-processing frameworks such as Spark or Hive, with experience building scalable data pipelines.
- Experience establishing ML foundations such as feature stores, DVC or other data-versioning tools, and model registry/versioning systems.
- Strong software engineering practices involving Git, CI/CD pipelines, code testing, and clean architecture.
- Strong written and verbal communication skills for collaboration with Data Scientists, product managers, and software engineering stakeholders.
- Preferred experience working with Data Scientists in applied research or advanced analytics environments.
- Preferred experience building and deploying forecasting, classification, or regression models.
- Preferred experience evaluating internal tooling and lightweight frameworks for Data Science workflows.
- Preferred e-commerce or supply-chain knowledge and experience delivering scalable engineering solutions with measurable business impact.
Tech Stack
Categories
Data EngineeringML Engineering
About Coupang
Coupang builds and operates a South Korea–focused e-commerce marketplace with an end-to-end logistics network (Rocket Delivery), plus food delivery, video streaming, and fintech under brands such as Coupang, Eats, and Play. Revenue comes from first-party retail, third-party marketplace services, advertising, and memberships (Rocket WOW). Founded in 2010, the company is headquartered in Seattle and is publicly listed on the NYSE (CPNG).