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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
The Taiwan Data, Analytics & AI team is the engine driving Coupang’s rapid expansion in the Taiwan market. Our mission is to transform massive datasets into actionable intelligence and automated systems that power business decisions. As we scale, we are transitioning from foundational growth to a sophisticated enterprise AI ecosystem. We are building the next generation of data services that ensure every stakeholder across the Taiwan organization has access to high-integrity, automated, and intelligent insights.
As a Staff Machine Learning Engineer, you will be a technical leader responsible for the architecture and automation of our regional data intelligence layer. Your primary focus will be bridging the gap between raw data and organizational knowledge. You will lead the automation of our Knowledge Base, govern the integrity of our core metrics, and scale our analytics services to support the entire Taiwan organization.
This is a high-impact role where technology meet business, and you will design systems that not only provide data but ensure that the "truth" behind the data is refreshed, accurate, and easily accessible through AI-driven interfaces and help us become true AI first Analytics Organisation.
What You Will Do
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Automated Knowledge Engineering: Design and implement end-to-end ML pipelines to automate the creation and maintenance of a centralized Knowledge Base, utilizing LLMs and RAG (Retrieval-Augmented Generation) to synthesize complex business logic.
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Metric Integrity & Governance: Develop systemic checks and automated validation frameworks to ensure the integrity of business metrics. You will be the architect of a "Single Source of Truth," ensuring definitions remain consistent across all AI and reporting services.
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AI-Driven Pipeline Automation: Architect "Self-Healing" data pipelines using AI tools to automate schema mapping, error detection, and recovery. Implement LLM-powered agents to generate, optimize, and document ETL code, reducing manual engineering overhead.
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Scalable AI Services: Architect and scale existing Data and Analytics services to handle the increasing demands of the entire Taiwan organization, ensuring high availability and low-latency access to insights.
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Feedback & Refresh Loops: Build automated feedback mechanisms to identify "stale" content or drifting metric definitions. You will design the workflows that ensure both new and existing knowledge content is refreshed regularly based on user behavior and data shifts.
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Systemic Optimization: Drive innovation in semantic retrieval and query understanding to allow non-technical stakeholders to interact with complex data layers using natural language.
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Enablement & Training: Act as a force multiplier by enabling and training various reporting functions (Finance, Ops, Marketing). You will create the tools and frameworks that allow these teams to self-serve with high confidence.
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Technical Mentorship: Lead by example in code quality, system design, and experimentation. Mentor senior and mid-level engineers, fostering a culture of technical excellence and continuous improvement.
Basic Qualifications
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Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related technical field.
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8+ years of professional experience in software engineering and applied machine learning (with at least 2 years in a Staff or Lead capacity).
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Proficiency in Python or Java, with deep experience building production-grade ML systems and scalable data pipelines.
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Strong experience with SQL and big data technologies (e.g., Spark, Presto/Trino, Airflow).
Preferred Qualifications
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Advanced Degree: Master’s or PhD in a relevant technical field.
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AI/LLM Expertise: Proven track record of deploying Large Language Models (LLMs), vector databases, and embedding-based retrieval systems in a production environment.
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Automated Management: Experience with AI-powered data management tools (e.g., automated data profiling, AI-driven data catalogs, or LLM-assisted SQL generation).
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Enterprise Scaling: Experience transitioning data organizations from "growth-phase" scripts to "enterprise-phase" robust microservices.
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Cloud Proficiency: Hands-on experience with AWS or GCP (SageMaker, Vertex AI, BigQuery).
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MLOps Mastery: Experience with ML lifecycle tools like MLflow, Kubeflow, or Weights & Biases to manage model lineage and data drift.
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Communication: Exceptional ability to communicate technical roadmaps to non-technical business leaders and influence cross-functional stakeholders in a fast-paced, global environment.
Type of work model
Details to consider
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