Senior ML Platform Engineer (Autonomous Driving)

About 42dot

42dot is a mobility AI company and the Global Software Center of Hyundai Motor Group, pioneering software-defined vehicles and autonomous driving technology. We develop safety-first, user-centric technologies that deliver continuous updates like smartphones, advancing a world where everything moves autonomously through intelligent urban transportation systems.

The Role

As a Senior ML Platform Engineer, you will architect and lead the core data and ML training/evaluation platforms powering cutting-edge autonomous driving algorithms. You'll develop distributed systems handling millions of scenes, build high-performance data serving SDKs, and significantly improve ML model development lifecycle efficiency across training, evaluation, deployment, and monitoring in cloud environments.

Key Responsibilities

• Set technical strategy and oversee development of high-scale, reliable data platforms to manage, visualize, and serve large-scale datasets for ML model training and validation
• Build data lakehouse infrastructure for autonomous driving scene datasets, including sensor data, calibration data, and annotation data
• Drive Autonomous Driving Data SDK development, including scene data search, dataset preparation, and dataset loading capabilities
• Identify and resolve performance bottlenecks across data processing pipelines, from data processing latency to test procedure coverage
• Bootstrap and maintain infrastructure for data platform components: data processing pipelines, databases, data lakehouses, and data serving systems
• Collaborate cross-functionally with ML algorithm, ML application, and cloud infrastructure teams to align platforms with overall autonomous driving system architecture

Required Qualifications

• Bachelor's degree or higher in Computer Science, Engineering, Robotics, or similar technical field
• Minimum 7 years of experience in Data Engineering or ML Platform roles
• Expert-level proficiency in Python with solid SDK development experience
• Strong working experience with databases (MongoDB, PostgreSQL, or equivalent)
• Deep understanding of modern AI frameworks (PyTorch, TensorFlow) with expertise in distributed data loaders for model training