search Browse Jobs
Senior ML Platform Engineer42dot · Pangyo (Software Dream Center), South Korea
42dot logo

42dot

company page ↗

Senior ML Platform Engineer

🗓️ Posted 2026-07-20 Pangyo (Software Dream Center), South Korea Fulltime Hybrid ICT
💰 Salary Not shared 📊 Market 6,666,667 KRW–10,833,333 KRW/mo

About the Company

ABOUT THE TEAM & MISSION 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)
  • ● Excellent leadership and communication skills, with a demonstrated ability to lead technical projects
  • ● Understanding data governance principles, data privacy regulations, and experience implementing security measures to protect data
  • ● Understanding of Large Models, like VLM
  • ● INTERVIEW PROCESS
  • ● Application Screening
  • ● First Interview (Virtual, approximately 1 hour)
  • ● Second Interview (In-person or Virtual, approximately 3 hours)
  • ● Offer Discussion / Onboarding
  • ● 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).
  • ● For application errors or inquiries, contact [email protected].
  • ● Veterans and applicants eligible for employment protection will receive preferential consideration in accordance with applicable laws and regulations.
  • ● In compliance with the Act on Employment Promotion and Vocational Rehabilitation for Persons with Disabilities, registered individuals with disabilities will receive preferential consideration.