Senior ML Engineer developing and scaling multitemporal, multimodal models for Earth observation using satellite imagery at LiveEO. The role involves applied research and engineering with real - world impacts.
About the role
- Senior Machine Learning Engineer developing deep learning models for radiological imaging applications. Focusing on designing and validating ML solutions to support accurate medical diagnoses with interdisciplinary teams.
Responsibilities
- 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.
Requirements
- Ph.D. or Master’s in Computer Science, Machine Learning, Engineering, Mathematics, or 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.
Benefits
- Use your personal benefits budget flexibly and choose the perks that suit you best!
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