자율주행 Data Flywheel을 구동하는 데이터와 소프트웨어 기반을 구축할 Senior ML Engineer를 찾습니다. AI/ML workflow, 도메인 지식, 확장 가능한 시스템을 연결하여 고품질 데이터를 더 쉽게 탐색하고 준비하며 활용할 수 있는 환경을 만듭니다.
🏢 About 42dot
대규모 자율주행 데이터와 분산 학습 인프라를 기반으로, 데이터의 탐색과 활용을 지능화하는 Data Intelligence 시스템을 개발하고 있습니다. 대규모 데이터 처리 및 ML 시스템의 성능 최적화부터 Data Ontology, Semantic Retrieval, AI Agent를 활용한 데이터 탐색·자동화 시스템 구축까지 다양한 기술적 도전에 참여할 수 있습니다.
🎯 The Role
Senior ML Engineer (AI Data) role at 42dot, focusing on building the data and software infrastructure for the autonomous driving Data Flywheel. You will connect AI/ML workflow, domain knowledge, and scalable systems to create an environment where high-quality data can be more easily explored, prepared, and utilized.
✅ Key Responsibilities
Develop common data models and interfaces: AD Data Ontology, canonical data model, SDK/API to provide consistent semantics and data access across various data platforms and ML workflows.
Implement AI/ML-based Data Intelligence and automation: Utilize semantic retrieval, LLM/VLM, AI Agent to automate data tasks and build reliable AI workflows in production environments.
Process AI/ML data and optimize training performance: Analyze bottlenecks in distributed processing, dataset preparation, storage access, and training data loading, improving throughput, resource utilization, and cost efficiency.
Design AI/ML system architecture: Understand AI/ML workflows from data collection to Auto-labeling and model training, designing supporting system architectures. Define components and interfaces according to technical requirements, considering reusability and scalability.
Build and operate production-level ML/Data systems: Build and operate systems for data·ML workloads in cloud-native environments, ensuring stability and operational efficiency through orchestration, reproducibility, monitoring, and failure recovery.
📌 Required Qualifications
Hold a bachelor's degree or higher in Computer Science, Electrical Engineering, Robotics, or related fields, or equivalent practical experience, with 7+ years of experience in AI/ML systems, data engineering, software architecture, and distributed processing.
Experience developing AI/ML·Data workflows and systems using programming languages like Python, C++, and designing/developing reusable SDKs, APIs, and libraries.
Understanding of model training and evaluation workflows based on ML frameworks like PyTorch, TensorFlow, with experience developing distributed training or large-scale dataset processing and training data loading systems.
Experience analyzing and optimizing performance bottlenecks such as storage I/O, CPU/GPU utilization, and memory usage based on understanding of ML/Data infrastructure and end-to-end data flow.
Experience designing system architectures that connect various Data/ML workloads, defining data flows and interfaces between systems in distributed environments.
Experience deploying and operating ML/Data workloads in cloud environments like AWS, GCP, Azure using Docker, Kubernetes, and applying workflow orchestration and monitoring.
⭐ Desirable Experience
Experience developing data processing technologies in Physical AI fields like Autonomous Driving, ADAS, Robotics using multimodal sensor data and map data.
Experience in Computer Vision, 3D Geometry, and Spatial Computing fields using technologies like coordinate transformation, camera geometry, and point cloud processing.
Experience developing complex domain data modeling and search systems using Ontology, knowledge graph, or embedding-based retrieval.
Experience developing and operating agentic workflows based on LLM/VLM or AI Agent, applying techniques like tool calling, MCP-based data service integration, agent orchestration, evaluation, and tracing.
Experience optimizing data supply performance in large-scale distributed learning environments using techniques like data loading, prefetching, caching, data sharding, and frameworks like Ray, Dask.
Experience designing and operating systems related to large-scale storage architecture, dataset lifecycle management, data lineage, privacy, or cross-region data governance.
🎁 Benefits
Competitive
🛂 Visa & Eligibility
국가보훈대상자 및 취업보호 대상자는 관계법령에 따라 우대합니다. 장애인 고용 촉진 및 직업재활법에 따라 장애인 등록증 소지자를 우대합니다.
