ML Data Engineer (m/f/d) - Computer Vision, Video & Sensor Data

What we offer

• Work in an international, agile team creating the future of autonomous systems
• Grow your career in a expanding and ambitious engineering team
• Build innovative products using state-of-the-art technologies in AI, robotics, and autonomy 
• Benefit from a steep learning curve and continuous development
• Enjoy team events and a strong, collaborative culture

Your mission

• Design and maintain high-throughput, scalable pipelines to ingest and organize large volumes of time-series camera and sensor data (RGB, IR, thermal, acoustic, depth, IMU).
• Own, curate, and continuously improve computer vision datasets for object detection and classification, ensuring high-quality, diverse, and statistically representative data.
• Build and operate active learning loops to prioritize high-value samples and accelerate dataset improvements.
• Write robust preprocessing and transformation pipelines using Python, NumPy, Pandas, and Albumentations for large-scale computer vision workloads.
• Manage labeling workflows, including automation, QA validation, annotation consistency checks, and dataset versioning.
• Collaborate with ML Engineers to fine-tune, train, and evaluate detection models, feeding insights back into data generation and selection.
• Analyze model weaknesses, blind spots, bias, and drift to derive actionable data improvements.
• Create internal tools and dashboards to visualize, audit, and analyze dataset quality, diversity, long-tail distributions, and model performance gaps.

Your profile

• Strong experience in Python and data processing frameworks (Pandas, NumPy, vectorized operations, multiprocessing).
• Hands-on experience building ETL/ELT pipelines for ingesting, transforming, and structuring large video and sensor datasets.
• Experience with data orchestration and lifecycle management for ML and computer vision workflows, including dataset versioning and reproducibility.
• Solid understanding of object detection pipelines (Detectron2, MMDetection, COCO format, bounding-box standards).
• Experience with active learning, uncertainty sampling, or semi-supervised dataset workflows.
• Familiarity with data annotation platforms (CVAT, Label Studio) and automated QA/consistency checks.
• Strong grasp of evaluation metrics for object detection (IoU, mAP, precision-recall curves, class-wise metrics).
• Comfortable with databases (SQL/NoSQL), file systems, and the management of large-scale image, video, and sensor datasets.
• Ability to work cross-functionally with perception, deployment, robotics, and data infrastructure teams.
• Fluent in English, German and/or French are a plus

Nice to have

• Experience with cloud storage and MLOps tools (AWS S3, MinIO, ClearML, MLFlow, Weights & Biases).
• Familiarity with ROS / robotics data formats (bag files, TF trees, sensor_msgs), Docker, or embedded ML workflows.
• Prior work with robotics, drones, or multi-sensor perception systems, including IR, LiDAR, radar, or audio datasets.

What else

• Outside-the-box creativity with a blend of conceptual and systematic design thinking.
• High intrinsic motivation, attention to detail, and strong problem-solving mindset.
• Structured, methodical, and reliable execution, even under uncertainty.
• Humble, collaborative, and mission-driven — values collective success over ego.
• High ethical standards and disciplined work ethic.
• Extra-curricular achievements, leadership, or unique projects are a plus.
• NATO-aligned nationality or close ally citizenship is required.

Why us?