Senior Machine Learning Engineer
Destinusgroup · Zürich, CH
Posted Nov 12, 2026
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About the job
Imagine building intelligent systems that don’t just work in perfect lab conditions, but
perform reliably in the real world, where uncertainty is the norm and failure is not an
option. As a Machine Learning Engineer, you will push the limits of computer vision by
designing, training, and validating neural networks that operate in complex, safety-critical
environments. Your work will directly influence how autonomous systems perceive and
interact with the world, combining deep learning, simulation, and rigorous verification into
one seamless pipeline.
At Destinus, we are shaping the future of defense through high-speed, autonomous flight
technologies. We develop next-generation unmanned aerial systems that deliver greater
speed, precision, and efficiency, supporting governments and defense organizations in
mission-critical operations worldwide. Daedalean AG, the AI and autonomy hub of the
Destinus Group, plays a key role in this vision. Developing safety-critical AI systems at the
intersection of advanced research and real-world aviation. Enabling machines to perceive,
understand, and make decisions in real time. Together, we combine aerospace
engineering and artificial intelligence to build the next generation of autonomous flight
systems, driving innovation where it matters most.
What You´ll Do
• Design, train, and optimize deep learning models for computer vision tasks in highly
dynamic and safety-critical environments
• Manage the development lifecycle of ML capabilities, from early-stage data
collection to the operational deployments of mature systems
• Develop robust evaluation pipelines to ensure models meet strict reliability and
safety requirements
• Leverage transfer learning and simulation to scale training and testing beyond realworld data limitations
• Collaborate closely with software, systems, and flight teams to integrate ML models
into real-world applications
• Continuously push model performance across edge cases, environmental
variability, and operational constraints
Requirements
Strong programming skills in C++ or Rust
• At least 5 years of hands-on experience in deep learning for computer vision
• Experience across the full ML stack, including model design, distributed training
frameworks, evaluation pipelines and resource-constrained inference platforms
• Experience with simulation environments or synthetic data generation is a strong
plus
• Experience with working with integrated sensors, including infrared cameras
• Master’s degree or PhD in computer science, physics, mathematics, or a related
technical field- or equal proven practical experience
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