Staff Machine Learning Engineer

About the role

Company Introduction:

Coupang is reimagining the shopping experience with the goal of wowing each customer from the instant they open the Coupang app to the moment an order is delivered to their door.

Our services in Taiwan include “Rocket Delivery” which offers next-day delivery for a wide selection of items at affordable prices, “Rocket Oversea” which offers free international delivery on millions of best-selling products from Korea, the U.S., and beyond.

We are looking for talents to help us lead Coupang’s expansion in Taiwan. This is an exceptional opportunity to become a part of Coupang’s growth in Taiwan and create a world where our customers wonder, “How did I ever live without Coupang?”

Role Overview:

This role is ideal for a pragmatic and impact-driven builder who is passionate about bridging the gap between data science and production systems. You will collaborate closely with Data Scientists to bring predictive models to life, establishing robust deployment pipelines, setting up foundational infrastructure, and driving MLOps best practices. The successful candidate will thrive in laying down technical foundations from scratch, ensuring scalability, maintainability, and high performance for our data and data science workflows.

What You Will Do:

- Collaborate closely with Data Scientists and Data Analysts to translate experimental code into production-ready architectures, driving code refactoring, model hosting decisions, and seamless integration.

- Design and formalize end-to-end model deployment processes, establishing standardized workflows for model versioning management to ensure reproducibility and reliability in production.

- Build and maintain robust data pipelines leveraging modern big data and distributed processing ecosystems, while establishing standardized Data Science development environments to boost cross-functional team productivity.

- Implement foundational ML infrastructure and standards, including feature store integration and data versioning management, tailored to support scalable business growth.

- Develop and operationalize predictive solutions using appropriate statistical, analytical, or heuristic approaches, when business needs require, bridging analytical insights with operational execution.

- Monitor, maintain, and optimize existing deployed solutions, proactively identifying bottlenecks, addressing technical debt, and ensuring high availability of production models.

Basic Qualifications

- Bachelor's/Master's degree in computer science, software engineering, industrial engineering, or any other quantitative disciplines, with 5+ years of relevant software/ML engineering experience in industry

- Hands-on experience in MLOps and model deployment lifecycle, including code refactoring, containerization (Docker, Kubernetes), and model hosting strategies (e.g., FastAPI, REST APIs, or cloud-native endpoints)

- Solid proficiency in Python, SQL, and distributed data processing frameworks (e.g., Spark, Hive, or equivalent big data technologies), with proven experience in building and maintaining scalable data pipelines