Senior ML Engineer (AI Data)

The role

This person will build data and software foundations to drive the autonomous driving Data Flywheel. They will create environments to easily explore, prepare, and utilize high-quality data by connecting AI/ML workflows, domain knowledge, and scalable systems.

What you will do

• Develop common data models and interfaces including AD Data Ontology, canonical data models, and SDK/API.
• Automate data tasks and build reliable AI workflows using Semantic retrieval, LLM/VLM, and AI Agent.
• Analyze and improve bottlenecks in distributed processing, dataset preparation, storage access, and training data loading.
• Design AI/ML system architectures supporting workflows from data collection to Auto-labeling and model training.
• Build and operate production-level ML/Data systems in cloud-native environments.
• Ensure stability and operational efficiency through orchestration, reproducibility, monitoring, and failure recovery.

Required qualifications

• Bachelor's degree or equivalent practical experience in Computer Science, Electrical/Electronic Engineering, Robotics, or related fields.
• 7+ years of experience in AI/ML systems, data engineering, software architecture, or distributed processing.
• Experience developing AI/ML and Data workflows and systems using Python or C++.
• Experience designing and developing reusable SDK, API, or library.
• Understanding of model training and evaluation workflows based on ML frameworks like PyTorch or TensorFlow.
• 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.
• Experience designing system architectures that connect various Data/ML workloads and defining interfaces in distributed environments.
• Experience deploying and operating ML/Data workloads using Docker and Kubernetes in cloud environments like AWS, GCP, or Azure.
• Experience applying workflow orchestration and monitoring.

Nice to have

• Experience developing data processing technology using multimodal sensor data and map data in Physical AI fields like Autonomous Driving, ADAS, or Robotics.
• Experience in Computer Vision, 3D Geometry, or Spatial Computing using coordinate transformation, camera geometry, or point cloud processing.
• Experience developing modeling and retrieval systems using Ontology, knowledge graph, or embedding-based retrieval.
• Experience developing and operating agentic workflows based on LLM/VLM or AI Agent including tool calling, MCP-based data service integration, agent orchestration, evaluation, and tracing.
• Experience optimizing data supply performance using data loading, prefetching, caching, or data sharding in large-scale distributed training environments, including using Ray or Dask.
• Experience designing and operating large-scale storage architecture, dataset lifecycle management, data lineage, privacy, or cross-region data governance systems.

Benefits

• Preferential treatment for persons eligible for national meritorious service.
• Preferential treatment for persons with disability registration.

Before you apply

• Document screening
• Online technical test
• 1st interview (video, approx. 1 hour)
• 2nd interview (in-person or video, approx. 3 hours)
• Employment may be canceled if false information is found in the application

About the company

42dot develops Data Intelligence systems that intelligentize data exploration and utilization based on large-scale autonomous driving data and distributed training infrastructure.