Machine Learning Scientist
Role details
Job location
Tech stack
Job description
We are looking for a Senior Machine Learning Scientist to lead machine learning strategy and deliver innovative modelling solutions for high-impact projects, ensuring scientific rigor and clinical relevance. About the Role You will turn research ideas into scalable products, contribute to publications and technical outputs, and uphold best practices in reproducibility and documentation. Working cross-functionally, you'll communicate insights clearly, collaborate on product development, and mentor others while helping to shape technical direction. Your daily duties will include:
- Lead ML strategy and technical execution for major projects.
- Design novel or advanced modelling approaches as needed.
- Contribute significantly to scientific or technical outputs such as publications, patents, or grant applications.
- Write, review, and take responsibility for technical documentation, reports, and algorithm specifications.
- Translate research concepts into proof-of-concepts, working prototypes and scalable solutions.
- Ensure reproducibility, documentation quality, and adherence to scientific and machine learning best practices.
- Collaborate with internal teams on product development.
Requirements
-
PhD in a relevant field, with industry experience.
-
Proficiency in Python and common ML libraries (e.g. PyTorch, TensorFlow, scikit-learn).
-
Proficiency with version control and good software engineering practices.
-
Deep expertise in machine learning and experimental methodology.
-
Strong track record of applied problem-solving.
-
Experience planning and delivering complex machine learning projects.
-
Ability to operate with minimal guidance in ambiguous problem spaces.
-
Evidence of significant research achievement. Desirable
-
Formal training or experience in relevant fields of biomedical imaging, e.g. MR, digital pathology, endoscopy.
-
Recognised expertise in a sub-domain (e.g. imaging, pathology, representation learning).
-
Experience with regulatory-facing evidence generation.
-
External scientific visibility.