We're looking for a highly driven Computer Vision / ML Engineer to own the data, training, evaluation, and MLOps lifecycle for our camera-based perception models. In this role, you'll turn real and synthetic drone data into reproducible, validated model releases, building and operating the pipelines that connect collection, annotation, training, evaluation, and release. This is an ownership role where you'll work closely with robotics perception engineers, directly shaping how reliably our systems see and understand the world.
The day-to-day
Requirements definition: define clear objectives, interfaces, datasets, and release standards for deep learning tasks such as detection, segmentation, and depth
Data strategy: drive real-world and synthetic data collection campaigns covering edge cases, rare conditions, and class imbalance
Dataset integrity: build trusted, versioned, auditable datasets, maintaining lineage and preventing leakage across every model release
Model performance: develop, train, and benchmark detection, segmentation, and depth-estimation models for aerial imagery
Evaluation rigor: set a high bar for evaluation and failure analysis across range, altitude, illumination, and weather conditions
MLOps ownership: build and operate the end-to-end pipeline for versioning, reproducible training, experiment tracking, and CI/CD
Deliver production-ready model artifacts. Export and optimize models for ONNX and TensorRT, validate accuracy and runtime performance.
You should apply if you
Computer vision depth: you have a deep understanding of CNN- and transformer-based architectures, training dynamics, and evaluation, with hands-on PyTorch experience
Dataset discipline: you're experienced building representative dataset splits, validating annotations, and conducting detailed failure analysis
MLOps experience: you have end-to-end production MLOps ownership, including experiment tracking, versioning, and CI/CD
Software engineering: you write clean, tested, maintainable code and make sound performance and algorithmic trade-offs
Track record: you bring 3+ years building and shipping computer-vision or ML systems with ownership across data, training, and evaluation
Education: you hold a degree in computer science, machine learning, or a related field – or equivalent hands-on experience that speaks louder than the diplom
Nice to haves
Aerial vision: experience with drone imagery, small-object detection, or low-light and low-resolution data
Simulation expertise: hands-on experience with NVIDIA Isaac Sim, Omniverse, or other synthetic-data workflows
Inference optimization: experience exporting and optimizing models with ONNX and TensorRT on NVIDIA Jetson hardware
What we offer
Real impact & ownership: Shape high-tech defense systems and take responsibility from day one.
Mission-driven environment: Work on technologies that matter for European security and sovereignty.
Competitive package: Competitive salary, EGYM Wellpass, corporate benefits, and equity options aligned with role and level.
Deep tech environment: Get hands-on experience with cutting-edge drone technology and real operational use cases.
Grow fast: Steep learning curve for juniors, strategic influence and leadership opportunities for seniors.
Startup mindset meets defence innovation: flat hierarchies, fast decisions, and space for your ideas.
Flexibility: Flexible hours, remote options, and relocation support.
Strong team: International, driven colleagues and a culture built on exchange, trust, and shared success.