Public summary
An international defense-technology startup specializing in machine vision seeks an ML Data Engineer to lead end-to-end data pipeline architecture and management for perception systems. The role involves designing scalable ingestion pipelines for multi-sensor data, driving dataset strategy for object detection, managing labeling workflows and QA, and collaborating across AI, robotics, and perception teams. The position requires 5+ years of experience with Python, data processing, ETL pipelines, object detection frameworks, and ML data lifecycle management. Fluent English is required; German or French language skills are a plus.
Location and work setup
- Location
- Munich
- Remote status
- Hybrid
- German requirement signal
- No German Required Detected
- Detected job language
- English
Responsibilities
Architect and own scalable pipelines for time-series multi-sensor data ingestion and preprocessing; drive dataset strategy ensuring quality and diversity for object detection datasets; design and operate active learning loops linking model performance to data selection; manage labeling workflows including tooling, QA, consistency, and coordination; collaborate with AI engineers to analyze model biases and translate findings into dataset improvements; plan and lead data collection campaigns to acquire real-world data; build internal tools and dashboards for dataset quality and performance visibility.
Qualifications
5+ years hands-on experience in Python and data processing frameworks (Pandas, NumPy); proven experience building and owning large-scale ETL/ELT pipelines for video and sensor data; expertise in data orchestration and ML/computer vision workflow lifecycle management; strong skills with object detection pipelines (e.g., Detectron2, MMDetection), dataset versioning, and evaluation metrics; experience with active learning and data annotation platforms (CVAT, Label Studio); knowledge of databases (SQL/NoSQL) and large-scale sensor dataset management; fluent in English with German or French as a plus; NATO-aligned citizenship or close ally required. Experience with cloud storage, MLOps tools, ROS, robotics data formats, and embedded ML workflows is beneficial.