Senior Machine Learning Engineer

• Advance the development of high-performance computer vision architectures to detect and diagnose medical conditions within complex radiological datasets (MRI, CT)
• Design and implement rigorous validation frameworks to ensure model robustness, clinical efficacy, and compliance with medical device certification standards
• Engineer solutions with clinical trust at the core, prioritizing model interpretability and uncertainty quantification to provide actionable insights for healthcare professionals
• Optimize scalable ML pipelines within a modern Docker and AWS ecosystem, ensuring a seamless transition from experimental research to production-grade deployment

• Ph.D. or Master’s in Computer Science, Machine Learning, Engineering, Mathematics, or a related quantitative field
• 3+ years of industry experience specifically focused on computer vision for medical applications
• Expertise in Python and PyTorch, with a deep understanding of medical image processing techniques and data formats
• Strong theoretical and practical understanding of modern computer vision architectures for 3D image segmentation and object detection (e.g. CNNs, ViT)
• Familiarity with at least two of the following areas: Self-supervised or semi-supervised learning, Computer vision foundation models, Anomaly detection, Active learning
• Proven ability to contribute to large-scale codebases and handle complex datasets in a collaborative environment
• Commitment to robust software engineering practices: including version control (Git), unit testing, CI/CD, and writing clean, maintainable code

Use your personal benefits budget flexibly and choose the perks that suit you best