Senior ML Platform Engineer (Autonomous Driving)

About the role

42dot is a mobility AI company committed to solving mobility challenges with software and AI. As the Global Software Center of Hyundai Motor Group, 42dot pioneers the future of mobility by advancing the development of software-defined vehicles. We develop safety-first, user-centric software-defined vehicle technologies that deliver the latest performance through continuous updates like smartphones. By advancing software and AI technology, 42dot envisions a world where everything is connected and moves autonomously through a self-managing urban transportation operating system. At 42dot, our AD ML Platform Engineers build the core data platform and ML training / eval platform for the cutting edge algorithms in autonomous driving. We develop the distributed system of a scalable data platform for large-scale dataset (millions of scenes), as well as high-performance data serving SDKs for ML model training / evaluation. The platforms we deliver could highly improve the efficiency of ML model development lifecycle, including training, evaluation, deployment, as well as monitoring in the cloud environment.

Responsibilities

• Set technical strategy and oversee development of high scale, reliable data platform to manage, visualize and serve large-scale datasets for ML model training and validation.
• Build up the data lakehouse for autonomous driving scene datasets, including the sensor data, calibration data, as well as annotation data
• Drive the Autonomous Driving Data SDK development, including scene data search, datasets preparation, dataset loading, etc.
• Dig into performance bottlenecks all along the data processing pipelines, from data processing latency, data search latency to Test Procedure (TP) coverage.
• Bootstrap and maintain infrastructure for Data Platform components-Data Processing Pipeline, Database, Data Lakehouse and Data Serving.
• Collaborate with cross-functional teams, including ML algorithm, ML application, and Cloud Infra to align ML Platforms with overall Autonomous Driving System Architecture.

Requirements

• Bachelor's degree or higher in Computer Science, Engineering, Robotics, or a similar technical field.
• Minimum of 7 years of experience in Data Engineering or ML Platform roles
• Expert-level proficiency in Python and solid experience in Python SDK development
• Solid working experience in Databases (e.g., MongoDB, PostgreSQL, etc)
• Strong understanding of modern AI frameworks (e.g., PyTorch, TensorFlow etc.), especially the principle of distributed data loader for model training
• Hands-on experience with data pipeline job orchestration with Databricks Workflows or Apache Airflow, as well as integrating data pipelines with machine learning models
• Extensive experience with data technologies and architectures such as Data Warehouse (e.g., Hive) or Lakehouse (e.g., Delta Lake)
• Experience with Apache Spark or other big data computing engines
• Excellent leadership and communication skills, with a demonstrated ability to lead technical projects
• Experience with autonomous vehicle sensor data (e.g., LiDAR, camera, radar)
• Experience with ML model training lifecycle (e.g., data preparation, model training / validation / deployment, etc)
• Understanding data governance principles, data privacy regulations, and experience implementing security measures to protect data
• Understanding of Large Models, like VLM
• Interview Process
• Application Review - Coding Test - 1st interview - 2nd interview - Offer Negotiation - Hiring
• The screening procedures may vary depending on the position, schedule, or other circumstances.
• You will be individually notified of the screening schedule and results via the email address provided in your application.

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