ML Data Engineer - Object Detection & Active Learning

• Design and maintain scalable pipelines to ingest and organize large volumes of time-series camera and sensor data (RGB, IR, acoustic, depth, IMU, and other modalities).
• Own and improve datasets for object detection and classification tasks, ensuring statistical robustness, diversity, and representativeness.
• Build and operate active learning loops to select high-value samples, reduce annotation cost, and continuously improve model performance.
• Write robust preprocessing pipelines using Python, NumPy, Pandas, and augmentation libraries like Albumentations.
• Manage labeling workflows, including QA rules, label consistency checks, vendor coordination, and dataset versioning.
• Collaborate with ML Engineers to fine-tune, train, and evaluate object detection models and feed insights back into the data pipeline.
• Analyze model weaknesses, uncover blind spots, and drive dataset improvements through statistical diagnostics and drift/bias detection.
• Create internal tools to visualize, audit, and analyze dataset quality, diversity, long-tail performance, and failure modes.

• Strong experience with Python and data-processing frameworks (Pandas, NumPy, multiprocessing).
• Familiarity with ETL/ELT pipelines for ingesting, transforming, cleaning, and structuring large video or sensor datasets.
• Experience with data orchestration and lifecycle management for ML workflows (preferably with high-bandwidth video/sensor workloads).
• Understanding of object detection pipelines and formats (COCO, Detectron2, MMDetection, label schemas).
• Experience with active learning, uncertainty sampling, or semi-supervised labeling workflows.
• Familiarity with annotation tools (CVAT, Label Studio) and quality-assurance processes.
• Solid understanding of model evaluation metrics (IoU, mAP, precision-recall, confusion matrix).
• Comfortable working with databases (SQL/NoSQL), file systems, and large-scale image/video dataset organization.
• Ability to collaborate effectively with perception, deployment, and robotics engineers across the product lifecycle.
• Fluent in English, German and/or French are a plus.

Nice to Have:

• Experience with cloud storage systems and MLOps platforms (AWS S3, MinIO, MLFlow, ClearML, Weights & Biases).
• Familiarity with ROS / robotics data formats (bag files, TF trees, sensor_msgs), Docker, or embedded ML stacks.
• Prior work with drone, robotics, or sensor-rich environments, including IR, LiDAR, radar, depth, or audio systems.

Meta:

• 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.
• Successful candidates must obtain security clearance., The world is changing. Exponential technologies are enabling new types of security threats. We are committed to staying ahead by building nimble, scalable, and cost-effective defences. We are looking for passionate developers who are eager to create exceptional products, safeguard our freedom, and strengthen the resilience of democracies.

Who we are: Autonomous Teaming is a defence-tech start-up specializing in machine vision solutions. Driven by cutting-edge innovation, our team works on next-generation technologies designed to meet rapidly evolving security challenges. What we do: We develop systems that enable computers and sensors to operate as coordinated teams, collaborating in real time to counter AI-powered asymmetric threats at scale - including drone swarms and other UXVs. Our mission is to build resilient, intelligent defence capabilities that perform reliably in the most demanding environments. Who we are: Based in Munich, Berlin, and Toulouse, we are expanding rapidly across Europe with plans to open additional office hubs. We value close, in-person collaboration as the foundation for building complex, high-impact technology, while maintaining flexibility aligned to role and team needs. Our culture is built on ownership, responsibility, and trust - with a shared commitment to growing and building together.   If you require alternative methods of application or screening, you must approach the employer directly to request this as Indeed is not responsible for the employer's application process.