Machine Learning Engineer optimizing personalization systems for Spotify's audio streaming service. Collaborating with cross - functional teams to enhance user experience and deliver recommendations.
About the role
- Machine Learning Engineer designing and optimizing deep learning models for safety-critical environments at Destinus. Shaping the future of high-speed, autonomous flight technologies.
Responsibilities
- Design, train, and optimize deep learning models for computer vision tasks in highly dynamic and safety-critical environments
- Own the full ML lifecycle, from data strategy and model architecture to deployment and performance monitoring
- Develop robust evaluation pipelines to ensure models meet strict reliability and safety requirements
- Work on ML certification activities, validating model behavior under defined regulatory frameworks
- Leverage transfer learning and simulation to scale training and testing beyond real-world 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
- Master’s or PhD in computer science, physics, mathematics, or a related technical field
- At least 5 years of hands-on experience in deep learning for computer vision
- Experience across the full ML stack, including model design, training pipelines, and evaluation systems
- Solid understanding of data-centric AI approaches, including dataset curation and augmentation strategies
- Experience with simulation environments or synthetic data generation is a strong plus
- Proven ability to tackle complex research problems over extended periods, in both academic and industrial settings
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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