About the Team & Mission
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
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Autonomous driving data visualization을 위한 Full-stack Web Application 설계 및 개발
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LiDAR, Camera Stream, Perception Label(Bounding Box, Lane Marker, Traffic Light 등), Trajectory 등 Multi-modal Data Visualization 구현
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React 기반 Frontend 및 Python / Node.js 기반 Backend API 개발
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대규모 Dataset 환경에서 Rendering 및 Backend 성능 최적화
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Data Loading, Preprocessing, Streaming을 위한 Backend Service 및 API 설계
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Autonomous Driving Algorithm Engineer와 협업하여 Model Output 및 Evaluation Metric Visualization 기능 개발
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기존 Open-source Visualization Framework 및 Tool(Rerun, Foxglove, WebViz 등)의 검토, Customization 및 Integration 수행
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Production 환경을 위한 Code Quality, Testing, Documentation 관리 및 개선
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Design and develop full-stack web applications for autonomous driving data visualization
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Develop synchronized multi-modal visualizations including LiDAR, camera streams, perception labels, and trajectory data
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Implement React-based frontends and Python/Node.js backend APIs for data workflows
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Optimize rendering and backend performance for large-scale datasets
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Design backend services and APIs for data loading, preprocessing, and streaming
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Collaborate with autonomous driving algorithm engineers to integrate model outputs and evaluation metrics into visualization tools
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Evaluate, customize, and integrate open-source visualization frameworks and tools such as Rerun, Foxglove, and WebViz
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Maintain high standards for code quality, testing, and documentation in production environments
Qualifications
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5년 이상의 Web Application 개발 경력
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React.js, Next.js, TypeScript 기반 Frontend 개발 경험
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Python(FastAPI/Flask), Node.js 기반 Backend 개발 경험
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WebGL, Three.js 등 3D Visualization 관련 개발 경험
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Docker, Git, REST API, CI/CD 기반 개발 경험
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3D 또는 Sequential Data 기반 Interactive UI/UX 개발 경험
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Code Review 및 Version Control 기반 협업 경험
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Python 또는 유사 Tool 기반 Data Processing 경험
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Computer Science, Software Engineering 또는 관련 분야 학사 학위 이상
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5+ years of hands-on experience developing web applications
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Experience with frontend development using React.js, Next.js, and TypeScript
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Experience developing backend systems using Python (FastAPI/Flask) and Node.js
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Experience with 3D visualization technologies such as WebGL and Three.js
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Experience with Docker, Git, REST APIs, and CI/CD workflows
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Experience designing interactive UI/UX for 3D or sequential data workflows
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Experience in collaborative environments using code review and version control
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Experience processing data using Python or similar tools
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Bachelor’s degree or higher in Computer Science, Software Engineering, or related fields
Preferred Qualifications
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Autonomous Vehicle, Robotics, Drone 등 실환경 Data Visualization Project 경험
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Sensor Data, Trajectory Data, Label Data 처리 및 Visualization 경험
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Rerun, Foxglove, WebViz 등 Open-source Visualization Tool Customization 경험
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Rosbag Data Format 및 관련 Visualization 경험
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WebSocket, gRPC, SSE 등 Real-time Data Streaming Framework 경험
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AWS, ArgoCD, Helm Chart 등 Cloud Deployment 경험
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Experience with real-world data visualization projects in autonomous vehicles, robotics, drones, or related domains
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Experience handling and visualizing sensor data, trajectory data, and label data
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Experience customizing open-source visualization tools such as Rerun, Foxglove, and WebViz
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Familiarity with Rosbag data formats and related visualization workflows
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Knowledge of real-time data streaming frameworks such as WebSocket, gRPC, and SSE
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Experience with cloud deployment tools and infrastructure such as AWS, ArgoCD, and Helm
Interview Process
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서류 전형
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코딩 테스트
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1차 면접 (화상, 1시간 내외)
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2차 면접 (대면 혹은 화상, 3시간 내외)
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처우 협의·입사
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Application Screening
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Coding / Assignment Test
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First Interview (Virtual, approximately 1 hour)
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Second Interview (In-person or Virtual, approximately 3 hours)
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Offer Discussion / Onboarding
Additional Information
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전형 절차는 일정 및 진행 상황에 따라 일부 변경될 수 있으며, 각 전형 결과는 등록하신 이메일로 개별 안내드립니다.
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지원서 접수 중 오류가 발생하거나 기타 문의 사항이 있을 경우, recruit@42dot.ai로 문의해 주시기 바랍니다.
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국가보훈대상자 및 취업보호 대상자는 관계법령에 따라 우대합니다.
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장애인 고용 촉진 및 직업재활법에 따라 장애인 등록증 소지자를 우대합니다.
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지원서 내용 중 허위 사실이 발견될 경우, 입사가 취소될 수 있습니다.
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인터뷰 프로세스 종료 후 지원자의 동의하에 평판조회가 진행될 수 있습니다.
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3개월의 수습기간이 적용될 수 있습니다.
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The recruitment process may change depending on schedule and progress; the result of each stage will be sent individually to your registered email.
Please do not include legally prohibited information in your application (e.g., ID number, family relations, marital status, salary, photo, physical details, hometown).
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For application errors or inquiries, contact recruit@42dot.ai.
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Veterans and applicants eligible for employment protection will receive preferential consideration in accordance with applicable laws and regulations.
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In compliance with the Act on Employment Promotion and Vocational Rehabilitation for Persons with Disabilities, registered individuals with disabilities will receive preferential consideration.
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42dot does not accept unsolicited resumes from search firms. We will not pay any fees for resumes submitted without prior agreement.
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False information in your application may result in offer cancellation.
A reference check may be conducted after the interview process, with your consent.
- A 3-month probationary period may apply.
