포티투닷
스타트업
Senior ML Platform Engineer
- 마감일
- 상시채용상시채용
- 근무지
- 경기 · 판교 (하이브리드)
- 홈페이지
- 42dot.ai
핵심 요약
- 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.
지원 자격
- 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
우대 사항
- 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
상세 내용
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.
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