AI Software Engineer (m/f/d)
fulltime_permanent mid_levelJob Overview
As an AI Software Engineer (m/f/d), you will be a key contributor within our development team. Your responsibilities include preparing and selecting data, training and validating models, as well as deploying them on real embedded UAVs, UGVs, and USVs to enhance their capabilities.
You will work within a world-class team to help push the boundaries of autonomous drone technology.
In this role, you collaborate closely with stakeholders from hardware development, testing, production, and customer operations, driving continuous improvements in the autonomy of our UxV platforms.
By advancing intelligent autonomy, you will actively support Quantum Systems’ mission to set the benchmark for next-generation UxV solutions.
Within this advertisment we are open to hiring people of all seniorities, from Junior to Lead, with the following profiles:
AI Engineer (Generalist)
Proven track record designing and training deep learning models for production use
Experience with model optimization for resource-constrained environments (quantization, pruning, distillation)
Deep expertise in computer vision architectures or LLMs Architecture
ML Platform Engineer (MLOps)
Experience building and maintaining ML training and inference pipelines
Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
Experience with GPU cluster management and high-performance computing environments
Data Engineer (Geospatial Data & Sensor Fusion)
Experience managing large-scale datasets, including geospatial, image, or sensor data
Familiarity with drone-generated data types (imagery, LiDAR, telemetry, flight logs)
Experience with data quality assurance, annotation workflows, and labelling platforms
Edge AI Engineer
Hands-on experience deploying AI models on embedded platforms (NVIDIA Jetson, ARM, FPGAs, or custom SoCs)
Experience with drone or robotics hardware and flight controller integration
Track record of optimizing inference latency and power consumption in edge environments