This position will be contracted through Boschs external vendor under a one-year agreement.
Department Information:
The EDS department focuses on software tooling development to support embedded products in the Advanced Driver Assistance System (ADAS) domain. We develop tools that streamline software and system development for technologies such as radar video and ultrasonic sensors. Serving global teams across Japan China Europe and Vietnam we contribute to the advancement of secure safe and intelligent mobility solutions.
We are seeking a skilled Data Engineer to build and optimize scalable data pipelines supporting AI/ADAS development. The role focuses on end-to-end data loop management data labeling workflows and high-quality data handling to enable robust machine learning systems.
Key Responsibilities
- Design and maintain scalable data pipelines for large-scale sensor data (camera radar lidar).
- Manage and optimize the AI data loop: data collection preprocessing labeling validation model feedback.
- Develop automation for data cleaning transformation validation and dataset versioning.
- Maintain and improve labeling workflows annotation standards and quality control processes.
- Collaborate with ML engineers to enhance data quality based on model performance.
- Ensure compliance with data governance privacy and security requirements.
- Contribute to CI/CD integration and automation of data workflows.
Qualifications :
Technical Requirements
- Strong proficiency in Python (mandatory) for data processing and automation.
- Experience with Pandas NumPy; knowledge of OpenCV is a plus.
- Experience with data pipeline tools such as Apache Airflow Spark Kafka (or similar).
- Solid knowledge of SQL and/or NoSQL databases.
- Experience with Git CI/CD concepts and Docker is an advantage.
- Familiarity with cloud platforms (AWS/Azure/GCP) or on-prem infrastructure.
Preferred Qualifications
- Experience handling ADAS / automotive sensor data.
- Knowledge of labeling tools (e.g. CVAT Labelbox Supervisely).
- Understanding of machine learning data lifecycle and active learning concepts.
- Experience working in a global cross-functional environment.
Additional Information :
Further details regarding benefits will be shared during the interview process
Remote Work :
No
Employment Type :
Full-time
This position will be contracted through Boschs external vendor under a one-year agreement.Department Information: The EDS department focuses on software tooling development to support embedded products in the Advanced Driver Assistance System (ADAS) domain. We develop tools that streamline software...
This position will be contracted through Boschs external vendor under a one-year agreement.
Department Information:
The EDS department focuses on software tooling development to support embedded products in the Advanced Driver Assistance System (ADAS) domain. We develop tools that streamline software and system development for technologies such as radar video and ultrasonic sensors. Serving global teams across Japan China Europe and Vietnam we contribute to the advancement of secure safe and intelligent mobility solutions.
We are seeking a skilled Data Engineer to build and optimize scalable data pipelines supporting AI/ADAS development. The role focuses on end-to-end data loop management data labeling workflows and high-quality data handling to enable robust machine learning systems.
Key Responsibilities
- Design and maintain scalable data pipelines for large-scale sensor data (camera radar lidar).
- Manage and optimize the AI data loop: data collection preprocessing labeling validation model feedback.
- Develop automation for data cleaning transformation validation and dataset versioning.
- Maintain and improve labeling workflows annotation standards and quality control processes.
- Collaborate with ML engineers to enhance data quality based on model performance.
- Ensure compliance with data governance privacy and security requirements.
- Contribute to CI/CD integration and automation of data workflows.
Qualifications :
Technical Requirements
- Strong proficiency in Python (mandatory) for data processing and automation.
- Experience with Pandas NumPy; knowledge of OpenCV is a plus.
- Experience with data pipeline tools such as Apache Airflow Spark Kafka (or similar).
- Solid knowledge of SQL and/or NoSQL databases.
- Experience with Git CI/CD concepts and Docker is an advantage.
- Familiarity with cloud platforms (AWS/Azure/GCP) or on-prem infrastructure.
Preferred Qualifications
- Experience handling ADAS / automotive sensor data.
- Knowledge of labeling tools (e.g. CVAT Labelbox Supervisely).
- Understanding of machine learning data lifecycle and active learning concepts.
- Experience working in a global cross-functional environment.
Additional Information :
Further details regarding benefits will be shared during the interview process
Remote Work :
No
Employment Type :
Full-time
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