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Coupang Internal

Staff AI Engineer

Seattle, USA; SeattleUnited States
Staff · Security & Privacy and Data Governance
POSTED 12 NOVVERIFIED 12M AGO
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Posted 12 Nov · n=64
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$236k–$279kno pay posted
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$236k–$279k
Seattle · n=9 · 365d to 10 Nov
CompanyCoupang Internal →
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987open · Staff ML / AI
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PythonJavaLLMsDistributed systems

Please complete the attached Internal Transfer Request Form and submit.

Please make sure to apply with your Coupang e-mail address.

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 Digital Trust Group at Coupang is the division responsible for safeguarding the company's global e-commerce platform through robust cybersecurity, data privacy engineering, and corporate IT security infrastructure. The group focuses on designing and implementing enterprise-wide security architectures—such as zero-trust access models, data loss prevention (DLP), and cloud security controls—while automating security processes to proactively mitigate risk across customer, merchant, and internal employee workflows.

What You Will Do

Build AI-Powered Investigation Systems

Develop AI workflows that automate investigation and analysis tasks.

Build agent-based systems that interact with internal tools, data sources, and knowledge repositories.

Improve reasoning quality, reliability, and performance of AI-driven workflows.

Implement human-in-the-loop review and feedback mechanisms.

Build Detection and Risk Analytics

Design and implement detection logic for suspicious or high-risk activity.

Develop risk signals, behavioral analytics, and anomaly detection capabilities.

Create systems that combine multiple telemetry sources into actionable intelligence.

Improve quality and coverage of existing detection capabilities.

Develop Data and Signal Pipelines

Build scalable batch and streaming pipelines for AI and analytics workloads.

Develop feature engineering workflows used by AI models and detection systems.

Create data products that support investigation, automation, and risk assessment.

Improve data quality, observability, and operational reliability.

Build Production AI Services

Design and implement APIs, backend services, and distributed systems that support AI applications.

Develop frameworks that make AI workflows easier to deploy, evaluate, and operate.

Monitor production systems and troubleshoot reliability or quality issues.

Participate in architecture discussions and contribute to technical design reviews.

Basic Qualifications

Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields

4 years of professional experience in applied machine learning

Experience in machine learning, deep learning, and statistical modeling

Proficiency in Python and/or Java, with experience in building production grade ML systems

Preferred Qualifications

Experience working with machine learning, AI, data-intensive systems, or analytics platforms.

Strong understanding of distributed systems and cloud-native architectures.

Experience designing APIs and scalable services.

Ability to independently drive projects from requirements through production deployment.

Experience with LLMs, RAG systems, or AI agents.

Source · Coupang InternalFirst seen 12 NovOriginal ↗