ML Data Engineer (m/f/d) - Sensor Data & Pipelines

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

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 — and will be expected to bring judgment and prior experience to how this is done, not just execute a defined process.

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 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?

Join us to shape the future of AI-driven defense!

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