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

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