이 공고, 이렇게 물어볼 겁니다

당신이 직접 구축하고 상용화한 로봇 시스템 중, 가장 복잡했던 '실시간 환경 인식(Perception)' 파이프라인을 설명하고, 이 과정에서 발생한 가장 큰 기술적 병목(bottleneck)과 이를 해결하기 위해 적용한 구체적인 알고리즘 개선(DNN/Pose Estimation) 사례를 숫자를 들어 설명해 주십시오.

🎯 실제 시스템 구축 경험과 기술적 깊이를 확인하며, 복잡한 문제를 해결하는 방법론을 검증한다.

귀하가 이끌었던 다국적 팀(미국/한국)에서, 충족되지 않은 운영 요구사항(Operational Requirements)을 구체적인 자동화 기회(ROI)로 전환하여 엔지니어링 로드맵을 수립했던 경험을 제시해 주십시오. 구체적으로 어떤 운영 데이터를 분석하여 어떤 자동화 프로젝트를 제안했고, 그 결과 달성한 ROI 수치는 얼마입니까?

🎯 기술적 이해를 넘어 비즈니스 목표(ROI)를 이해하고 이를 기술 전략으로 전환하는 능력을 평가한다.

수백 대의 로봇이 동시에 작동하는 대규모 물류 환경에서, 센서 보정(Calibration) 및 실시간 위치 추정(Pose Estimation) 오류를 최소화하기 위해 MLOps 파이프라인과 하드웨어 제어 시스템을 어떻게 통합하여 안정적인 운영을 보장했는지, 구체적인 시스템 설계와 실패 사례를 중심으로 설명해 주십시오.

🎯 대규모 시스템에서의 안정성과 엔지니어링 통합 능력, 특히 MLOps와 하드웨어 간의 복잡한 상호작용 능력을 확인한다.

귀하가 리드했던 조직에서, 연구(Research) 단계의 혁신적인 기술을 실제 생산 규모(Production Scale)의 자동화 시스템으로 전환하는 과정에서, 기술적 이상과 운영적 현실 사이의 괴리를 어떻게 관리하고 팀원들의 동기 부여를 유지했는지, 그리고 초기 프로토타입에서 상업적 제품으로 출시하기까지의 평균 소요 시간(Cycle Time)은 얼마였습니까?

🎯 연구와 상업화 사이의 간극을 관리하고, 빠른 속도와 현실적인 제약 조건 속에서 팀을 이끌어내는 '스타트업 마인드'와 실행력을 검증한다.

최근 경쟁사 대비 Coupang의 로봇 기술 우위를 확보하기 위해, 귀하가 외부 학계나 산업 파트너와 협력하여 기술적 리더십을 구축했던 구체적인 사례와, 이를 통해 확보한 특허 또는 주요 기술 제휴의 영향력을 설명해 주십시오.

🎯 외부 소통 능력과 기술을 시장/학계에 선도적으로 제시하는 '기술 리더(Thought Leader)'로서의 역량을 확인한다.

질문만 읽으면 컨닝이에요. 소리 내어 답해보세요 — 어디서 틀어지는지 짚어드립니다.

공고 내용

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 ecommerce 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 entrepreneurial 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.

Job Overview

Global Operations Automation and Robotics Technology (GO ART) is the Zero-One organization within Coupang chartered to design, build, and deploy the most advanced fulfillment and transportation automation and robotics solutions in the industry. We are transforming Coupang's logistics network through in-house robotics, computer vision, and AI — at a scale and speed unmatched in Asian e-commerce. The team is based in Mountain View, Seattle, and Seoul.

We are looking for a Senior Director of Robotics Computer Vision to lead the technical strategy, organization, and delivery of GO ART's robotic perception and manipulation programs end-to-end. This executive is the single technical owner for how Coupang's fulfillment centers see, reason about, and physically interact with the world.

The right candidate is a player-coach technology leader who has personally built and shipped robotic perception or manipulation systems at production scale, and who has subsequently grown and led multi-team organizations (engineers, applied scientists, and hardware/integration partners) that deliver against aggressive operational milestones. They are equally comfortable presenting a research roadmap to executives, debugging a 6-DoF pose-estimation pipeline on the floor of an FC, and recruiting world-class talent into a fast-moving Zero-One environment.

Key Responsibilities

· Own the technical vision and multi-year roadmap for robotic perception, manipulation, and CV-driven automation across Coupang's global fulfillment and logistics network.

· Build and lead the org — multiple teams of CV engineers, robotics engineers, applied scientists, and ML engineers across the U.S. and Korea. Hire, mentor, and develop senior IC and management talent.

· Set the bar for technical excellence in real-time perception (2D/2.5D/3D sensing, DNN-based detection/tracking/recognition, pose estimation, 3D reconstruction, sensor calibration) and robotic manipulation (grasping, picking, packing, induction, sortation).

· Drive cross-functional execution with hardware, controls, simulation, MLOps, fleet software, and operations teams to deliver integrated systems from prototype to production deployment at scale.

· Translate operational requirements into engineering programs — partner with FC operations, industrial engineering, and supply-chain leaders (largely KST-based) to identify the highest-ROI automation opportunities and ship against them.

· Represent Coupang externally as a technical thought leader in robotics and CV: conferences, publications, partnerships with academia, and senior-level vendor/partner engagements.

· Operate with a startup mindset — comfortable under ambiguity, hands-on when the problem demands it, and relentless about converting research into deployed, reliable, cost-effective systems.

Basic Qualifications

· PhD in Computer Science, Electrical Engineering, Robotics, Computer Vision, AI/ML, or a closely related discipline (or MS with equivalent industry depth).

· 12+ years of experience developing and shipping production robotics, computer vision, or robotic perception systems — including hands-on technical contribution earlier in career.

· 6+ years leading engineering organizations, with demonstrated experience managing managers and scaling teams of 30+ across multiple locations.

· Track record of delivering at least one large-scale robotics or CV automation program from concept to wide production deployment (warehouse automation, autonomous systems, manufacturing robotics, or comparable).

· Deep expertise in modern computer vision and deep learning: real-time DNN architectures, 2D/3D object detection, tracking, recognition, 6-DoF pose estimation, 3D data processing, automa

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