Machine Learning Engineer

The position is a Machine Learning Engineer at Destinus, a company that creates high‑speed, autonomous unmanned aerial systems for defense and government missions worldwide. Within the Destinus Group, the AI and autonomy unit Daedalean AG focuses on safety‑critical artificial‑intelligence solutions that enable aircraft to perceive, understand, and act in real time. In this role you will devise, train, and fine‑tune deep‑learning models for computer‑vision challenges that arise in fast‑moving, safety‑critical settings. You will manage the entire machine‑learning pipeline—from data strategy and model architecture through deployment and ongoing performance monitoring—while building rigorous evaluation processes that satisfy strict reliability and safety standards. The job also involves contributing to certification work, using transfer learning and simulation to extend training beyond limited real‑world data, and working hand‑in‑hand with software, systems, and flight teams to embed the models into operational platforms. Candidates must possess strong programming abilities in C++ or Rust and hold a Master’s or PhD in computer science, physics, mathematics, or a closely related discipline. At least five years of practical experience in deep‑learning for computer vision, covering model design, training pipelines, and evaluation frameworks, is required. A solid grasp of data‑centric AI practices, including dataset curation and augmentation, is essential, as is a proven track record of solving complex research problems in both academic and industrial environments. Experience with simulation environments or synthetic data generation is considered a valuable addition. The role emphasizes a mindset of tackling hard, ambiguous problems, delivering systems that must operate reliably every time, and continuously improving performance across edge cases, environmental variations, and operational limits.