Machine Learning Scientist

  • Technology
  • Cambridge, United Kingdom

Machine Learning Scientist

Job description

Cyted's mission is to revolutionise diagnostic methods to build a world where disease is prevented rather than treated. We focus on providing digital diagnostic infrastructure to drive the earlier detection of disease. Our technologies use artificial intelligence and novel biomarkers to unlock clinical insight and improve patient outcomes.
The Cyted group develops and deploys digital diagnostic services for research and clinical use. Our services are designed to dignify and empower, placing patients at the heart of our services. 


Cyted is seeking a Machine Learning Scientist to join our amazing team. The Machine Learning Scientist will play a crucial role in building new systems to provide medical insights and manage diagnostic workflows. The technologies will include unique new machine learning technology, highly scalable online services and web/mobile apps. The Machine Learning Scientist will be part of a team responsible for developing our cloud-based diagnostics platform, as well as rapid prototypes and proofs of concept.  The Machine Learning Scientist will plan and scale deep learning technologies for medical data with a focus on images.


Responsibilities:

  • Building reusable code and libraries for future use
  • Designing and delivering new platform capabilities
  • Validating and deploying machine learning models developed in Python with packages such as PyTorch and TensorFlow
  • Integrating with cloud APIs and data services
  • Taking part in Agile and Continuous Improvement processes
  • Contributing to the culture of our inclusive and enthusiastic team


Working pattern, location and salary:

The role is a full-time position with a standard 37.5 hour working week. The role holder may be required to work flexibly.

The Machine Learning Scientist will be based at the Cyted’s Head Office, WeWork, 50-60 Station Road, Cambridge, CB1 2JH and may need to visit other company sites if and when required.

Competitive salary.


Benefits:

  • 25 days holiday per holiday year, plus public holidays
  • Pension scheme
  • Share options
  • Personal development budget
  • Health, dental, hearing and eye insurance
  • Life insurance and critical illness cover
  • Perks at work scheme
  • Cycle to work scheme
  • Free refreshments
  • A knowledgeable, high-achieving, experienced and fun team
  • The chance to be part of a growing start-up, the next leader in building integrated diagnostics by combining molecular biomarkers with digital solutions

Job requirements

Qualifications and background:

  • Msc or PhD degree in Computer Science, or related technical, maths, or scientific field
  • Strong theoretical background on statistics, Bayessian methods, deep probabilistic models
  • Publications in the area of machine learning or medical imaging (desirable)
  • Prior industry experience in ISO regulated environments (desirable)

Experience:

  • Extensive hands-on experience with deep learning, machine learning, and computer vision
  • Familiarity with machine learning methods for handling sparse data and confidence estimation
  • Demonstrable experience in machine learning frameworks such as, Tensorflow and Tensorflow probability, scikit-learn and Keras
  • Experience with Python
  • Experience with handling large datasets
  • Experience with CI/ CD and data version control
  • Experience with Digital Pathology frameworks, tools and libraries (desirable)
  • Familiarity with AWS SageMaker (desirable)

Knowledge, skills and abilities:

  • Strong understanding of a relevant healthcare area - medical imaging, digital pathology, bioinformatics, population health or other related area
  • Hard working, detail oriented, team player
  • Ability to think creatively and solve problems working closely with system users, software developers and other business stakeholders
  • Strong communication skills in written and spoken English


Please contact hr@cyted.ai if you have any questions in relation to this role.

Reference: RCYTHQ0040