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Senior AI/ML Data Engineer – Robotics & Drones (m/w/x)
Transforming raw sensor recordings into high-quality datasets for robotics AI/ML. Python proficiency and large-scale sensor data handling experience required. Automated data pipelines, scalable workflows, and data quality management focus.
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Anforderungen
- Master's degree in CS, Data Engineering, Robotics, SE, EE, or related technical field, or equivalent practical experience
- Strong Python proficiency and production-quality software development
- Experience with data engineering frameworks, ETL workflows, and distributed processing systems
- Handling large-scale sensor data (cameras, radar, LiDAR, IMU, GNSS, or similar)
- Strong understanding of data quality management, validation, and pipeline monitoring
- Experience with dataset versioning, reproducibility, and data lineage concepts
- Strong Linux environments knowledge and software development best practices
- Experience with cloud (Azure, AWS, or similar) or distributed computing environments
- Strong analytical and problem-solving skills
- Excellent communication skills and collaboration across multidisciplinary engineering teams
- Experience in robotics, autonomous systems, autonomous vehicles, drones, AMRs, or related domains
- AI/ML data preparation, dataset curation, and training data management
- Familiarity with annotation workflows, ground-truth generation, and sensor calibration processes
- Experience with DVC, MLflow, Airflow, Spark, Kubernetes, or similar platforms
- Building data quality dashboards and analytics solutions (Grafana, Power BI, Tableau, Plotly, or equivalent)
- Knowledge of data lake architectures and large-scale storage systems
- Experience with ROS/ROS2 and robotic data recording formats
- Supporting ML training workflows and model evaluation infrastructure
- Familiarity with MLOps and DataOps practices
- Experience in fast-paced start-up or incubation environments
- Systems Thinker understanding data flow in complex robotics and AI/ML ecosystems
- Ownership Mentality with focus on reliability, quality, and operational excellence
- Automation Advocate eliminating manual processes through scalable engineering solutions
- Data-Driven Problem Solver using metrics and evidence for improvements
- Collaborative Influencer working effectively across software, ML, robotics, and infrastructure teams
Aufgaben
- Own end-to-end data processing and dataset lifecycle for AI/ML systems
- Transform raw sensor recordings into reliable, high-quality datasets
- Build robust, scalable, and automated data pipelines
- Design, develop, and maintain automated data processing pipelines
- Establish scalable and reproducible workflows for AI/ML development
- Drive continuous improvements in pipeline reliability and performance
- Own lifecycle management of datasets for AI/ML model development
- Define and automate dataset creation processes for model training and validation
- Ensure dataset traceability, reproducibility, and version control
- Define and implement automated quality checks for data processing
- Verify data correctness, completeness, and integrity after processing
- Identify data quality issues and drive corrective actions
- Manage distribution of datasets across file systems and cloud environments
- Optimize large-scale dataset storage, transfer, and access
- Support compute platforms for AI/ML training and evaluation
- Develop dashboards and reporting solutions for data KPIs
- Monitor data size, growth, and quality
- Monitor coverage of operational scenarios
- Monitor label and ground-truth quality
- Monitor AI/ML readiness KPIs
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Von Nejo automatisch aufbereitet
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Zur Originalanzeige bei DEU Aptiv Services Deutschland GmbHÜber das Unternehmen
The company is a global leader in low and high voltage power and signal distribution systems for electrified, automated, and connected vehicles.
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