[We Are A Mobility AI Company] 42dot은 소프트웨어와 AI 기술로 service-defined과 safety-designed 가치를 중심으로 한 SDV (software-defined vehicle)를 만들고 있습니다. 2022년 8월 현대자동차그룹의 소프트웨어 관련 사업 역량을 강화하는 목표로 그룹의 멤버가 된 42dot은 SDV 기술을 기반으로 자율주행 및 모빌리티 솔루션과 서비스를 제공하고 있습니다. [42dot 기사]

https://www.hankyung.com/article/202401118201g

[42dot 영상]

https://www.youtube.com/watch?v=KX5FVReOdNg

https://www.youtube.com/watch?v=xL56nsH585s

[We are looking for the best] 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.

• Develop a high scale, reliable data platform to manage, visualize, search and serve large-scale datasets for ML model training, fine tune and validation. • Develop advanced autonomous driving data SDK, including scene data search, datasets preparation, dataset loading, etc. • Build up the data lakehouse for autonomous driving scene dataset, including the sensor data, calibration data, as well as annotation data • 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.

• Bachelor's degree or higher in Computer Science, Engineering, Robotics, or a similar technical field. • Minimum of 5 years of experience in Data Engineering or ML Platform roles • Proficient in Python and solid experience in Python SDK development • Solid working experience in Databases (e.g., MongoDB, PostgreSQL, etc) • 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

• 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 of modern AI frameworks (e.g., PyTorch, TensorFlow etc.) • Understanding data governance principles, data privacy regulations, and experience implementing security measures to protect data

• 서류전형 - 코딩테스트 - 화상면접 (1시간 내외) - 대면 혹은 화상면접 (3시간 내외) - 최종합격 • 전형절차는 직무별로 다르게 운영될 수 있으며, 일정 및 상황에 따라 변동될 수 있습니다. • 전형일정 및 결과는 지원서에 등록하신 이메일로 개별 안내드립니다.

• 이력서 제출 시 주민등록번호, 가족관계, 혼인 여부, 연봉, 사진, 신체조건, 출신 지역 등 채용절차법상 요구 금지된 정보는 제외 부탁드립니다. • 인터뷰 프로세스 종료 후 지원자의 동의하에 평판조회가 진행될 수 있습니다. • 국가보훈대상자 및 취업보호 대상자는 관계법령에 따라 우대합니다. • 장애인 고용 촉진 및 직업재활법에 따라 장애인 등록증 소지자를 우대합니다.