Senior ML Platform Engineer – Autonomous Driving

42dot

Senior ML Platform Engineer focusing on ML training and evaluation platforms at 42dot. Developing scalable data solutions for autonomous driving algorithms and large-scale datasets.

Posted 7/20/2026full-time🇰🇷 South KoreaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining high-scale data platforms, with a strong focus on data processing pipelines, database management, and integration with machine learning models. Proven ability to lead technical projects and collaborate effectively with cross-functional teams in the autonomous driving domain.

Highest-signal resume keywords

Python SDK DevelopmentData Pipeline Job OrchestrationData Technologies and ArchitecturesMachine Learning FrameworksLeadership and Communication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData Processing PipelineDatabase ManagementData LakehouseMachine Learning IntegrationDistributed Data LoaderBig Data ComputingData WarehouseData SDK DevelopmentPerformance Optimization

Soft Skills

LeadershipCommunication

Tools & Technologies

Databricks WorkflowsApache AirflowMongoDBPostgreSQLPyTorchTensorFlowApache SparkDelta LakeHive

Industry Keywords

Autonomous DrivingData PlatformML Model TrainingData VisualizationData Processing Latency

Tech Stack

Tools & technologies

AirflowApacheBootstrapCloudMongoDBPostgresPythonPyTorchSparkTensorflow

About the role

Key responsibilities & impact

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

What you’ll need

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.

Benefits

Comp & perks

The recruitment process may change depending on schedule and progress; the result of each stage will be sent individually to your registered email.
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.
3-month probationary period may apply.
False information in your application may result in offer cancellation.
A reference check may be conducted after the interview process, with your consent.