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

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

Data Engineering & Architecture Full-Time

ML Data Engineer (m/f/d) - Sensor Data & Pipelines: our view in 3 lines...

  • The Role:This is a senior data engineering role focused on building data pipelines for sensor data and perception systems in AI-driven defense and robotics.
  • The Person:The person will architect and own ingestion and preprocessing pipelines, shape dataset strategy, run active learning loops, manage labeling QA, and build tools and dashboards for dataset quality and performance gaps.
  • Requirements:The ideal candidate has 5+ years of hands-on experience in Python and data processing frameworks, plus ETL/ELT pipelines, dataset versioning, object detection pipelines, and data annotation platforms.

About the role

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!

Published September 16, 2026
Location Munich, Germany
Job Type Full-Time