What we offer
Work in an international, agile team creating the future of autonomous systems. Grow your career in an expanding and ambitious engineering team, building innovative products using state-of-the-art technologies in AI, robotics, and autonomy.
Your mission
This role owns the data foundation of our perception systems end-to-end — the layer that directly determines model performance in real-world environments. You'll set the technical direction for how we collect, curate, and continuously improve the datasets behind object detection, working as a senior technical partner to ML, perception, and robotics teams, turning raw, messy sensor data into reliable, production-grade systems at scale.
You will take full ownership of the ML data lifecycle, from architecture decisions on ingestion and pipelines, through labeling strategy and QA, to driving continuous, metrics-informed dataset improvement.
What you'll do
- Architect and own scalable pipelines for ingesting, organizing, and preprocessing large volumes of time-series camera and multi-sensor data (RGB, IR, thermal, depth, IMU).
- Drive the strategy behind our object detection datasets, ensuring quality, diversity, and statistical representativeness at scale.
- Design and operate active learning loops that connect model performance directly to data selection and improvement priorities.
- Own labeling workflows end-to-end — tooling decisions, QA methodology, consistency standards, and coordination of annotation efforts.
- Partner closely with AI Engineers to diagnose model weaknesses, bias, and drift, and translate findings into concrete dataset strategy.
- Plan and lead data collection campaigns (field recordings, drone/video capture) to close gaps with high-value real-world data.
- Build internal tools and dashboards that give the org visibility into dataset quality, distribution, and performance gaps.
Your profile
- 5+ years of hands-on experience in Python and data processing frameworks (Pandas, NumPy, vectorized operations, multiprocessing).
- Proven track record building and owning ETL/ELT pipelines for large-scale video and sensor datasets in production.
- Deep experience with data orchestration and lifecycle management for ML/computer vision workflows, including dataset versioning and reproducibility.
- Strong command of object detection pipelines (Detectron2, MMDetection, COCO format, bounding-box standards).
- Demonstrated experience designing active learning, uncertainty sampling, or semi-supervised dataset workflows.
- Deep familiarity with data annotation platforms (CVAT, Label Studio) and building automated QA/consistency checks.
- Strong grasp of evaluation metrics for object detection (IoU, mAP, precision-recall curves, class-wise metrics).
- Comfortable owning decisions around databases (SQL/NoSQL), file systems, and large-scale image, video, and sensor dataset management.
- Track record of working cross-functionally and influencing 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 a strong problem-solving mindset. NATO-aligned nationality or close ally citizenship is required.