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AD Division의 Senior Data Visualization Engineer는 Autonomous Driving Dataset을 위한 Web 기반 Visualization Platform을 설계하고 개발합니다. 대규모 주행 데이터와 다양한 센서 정보를 효율적으로 시각화하고 분석할 수 있는 Full-stack Application을 구축하며, 이를 통해 Autonomous Driving Algorithm 개발 및 Debugging Workflow를 지원합니다. 또한 Perception, Planning, Data Engineering 팀과 긴밀히 협업하여 3D Point Cloud, Camera Stream, Perception Label, Trajectory 등 다양한 Multi-modal Data를 직관적으로 분석할 수 있는 고성능 Visualization System 개발 업무를 수행합니다.

The Senior Data Visualization Engineer in the AD Division designs and develops web-based visualization platforms for autonomous driving datasets. This role focuses on building full-stack applications for rendering and analyzing large-scale multi-modal data, including 3D point clouds, camera streams, perception labels, trajectories, and other algorithm-related data. You will collaborate closely with perception, planning, and data engineering teams to develop high-performance visualization systems that accelerate autonomous driving algorithm development, triage, and debugging workflows.

Responsibilities

• Autonomous driving data visualization을 위한 Full-stack Web Application 설계 및 개발

• LiDAR, Camera Stream, Perception Label(Bounding Box, Lane Marker, Traffic Light 등), Trajectory 등 Multi-modal Data Visualization 구현

• React 기반 Frontend 및 Python / Node.js 기반 Backend API 개발

• 대규모 Dataset 환경에서 Rendering 및 Backend 성능 최적화

• Data Loading, Preprocessing, Streaming을 위한 Backend Service 및 API 설계

• Autonomous Driving Algorithm Engineer와 협업하여 Model Output 및 Evaluation Metric Visualization 기능 개발

• 기존 Open-source Visualization Framework 및 Tool(Rerun, Foxglove, WebViz 등)의 검토, Customization 및 Integration 수행

• Production 환경을 위한 Code Quality, Testing, Documentation 관리 및 개선

• Design and develop full-stack web applications for autonomous driving data visualization

• Develop synchronized multi-modal visualizations including LiDAR, camera streams, perception labels, and trajectory data

• Implement React-based frontends and Python/Node.js backend APIs for data workflows

• Optimize rendering and backend performance for large-scale datasets

• Design backend services and APIs for data loading, preprocessing, and streaming

• Collaborate with autonomous driving algorithm engineers to integrate model outputs and evaluation metrics into visualization tools

• Evaluate, customize, and integrate open-source visualization frameworks and tools such as Rerun, Foxglove, and WebViz

• Maintain high standards for code quality, testing, and documentation in production environments

Qualifications

• 5년 이상의 Web Application 개발 경력

• React.js, Next.js, TypeScript 기반 Frontend 개발 경험

• Python(FastAPI/Flask), Node.js 기반 Backend 개발 경험

• WebGL, Three.js 등 3D Visualization 관련 개발 경험

• Docker, Git, REST API, CI/CD 기반 개발 경험

• 3D 또는 Sequential Data 기반 Interactive UI/UX 개발 경험

• Code Review 및 Version Control 기반 협업 경험

• Python 또는 유사 Tool 기반 Data Processing 경험

• Computer Science, Software Engineering 또는 관련 분야 학사 학위 이상

• 5+ years of hands-on experience developing web applications

• Experience with frontend development using React.js, Next.js, and TypeScript

• Experience developing backend systems using Python (FastAPI/Flask) and Node.js

• Experience with 3D visualization technologies such as WebGL and Three.js

• Experience with Docker, Git, REST APIs, and CI/CD workflows

• Experience designing interactive UI/UX for 3D or sequential data workflows

• Experience in collaborative environments using code review and version control

• Experience processing data using Python or similar tools

• Bachelor’s degree or higher in Computer Science, Software Engineering, or related fields

Preferred Qualifications

• Autonomous Vehicle, Robotics, Drone 등 실환경 Data Visualization Project 경험

• Sensor Data, Trajectory Data, Label Data 처리 및 Visualization 경험

• Rerun, Foxglove, WebViz 등 Open-source Visualization Tool Customization 경험

• Rosbag Data Format 및 관련 Visualization 경험

• WebSocket, gRPC, SSE 등 Real-time Data Streaming Framework 경험

• AWS, ArgoCD, Helm Chart 등 Cloud Deployment 경험

• Experience with real-world data visualization projects in autonomous vehicles, robotics, drones, or related domains

• Experience handling and visualizing sensor data, trajectory data, and label data

• Experience customizing open-source visualization tools such as Rerun, Foxglove, and WebViz

• Familiarity with Rosbag data formats and related visualization workflows

• Knowledge of real-time data streaming frameworks such as WebSocket, gRPC, and SSE

• Experience with cloud deployment tools and infrastructure such as AWS, ArgoCD, and Helm

Interview Process

• 서류전형 - 코딩테스트 - 화상면접 (1시간 내외) - 대면 혹은 화상면접 (3시간 내외) - 최종합격

• 전형절차는 직무별로 다르게 운영될 수 있으며, 일정 및 상황에 따라 변동될 수 있습니다.

• 전형일정 및 결과는 지원서에 등록하신 이메일로 개별 안내드립니다.

• Resume Screening - Coding Test - Virtual Interview (approximately 1 hour) - Onsite or Virtual Interview (approximately 3 hours) - Final Offer

• Please note that the interview process may vary depending on the position and is subject to change based on scheduling and other circumstances.

• Interview schedules and results will be communicated individually via the email address provided in your application.

Additional Information

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• 3개월의 수습기간이 적용될 수 있습니다.

   

• Please upload all required documents in PDF format.

• Veterans and applicants eligible for employment protection will receive preferential consideration in accordance with applicable laws and regulations.

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