Machine Learning Engineer

Science · Cambridge, Cambridgeshire
Department Science
Employment Type Full-Time

About us

Cydar Medical innovates in the healthcare software space. We connect live images from the hospital operating rooms to the power of cloud computing. Our software guides physicians during complex endovascular procedures, which results in better outcomes for patients.  Our product, Cydar EV, is used in innovative hospitals across Europe and United States, providing us with a stream of data, which we use to constantly improve our algorithms. Our solutions address real clinical needs, and we are motivated by seeing how our algorithms improve patients’ lives. We are pushing the boundaries of technology and user experience to deliver a product which is revolutionising keyhole surgery.  

 

As a member of the Science team, you will be creating state-of-the-art tools which help clinicians make the best, data-driven decisions for their patients. We can accommodate applicants with varying levels of experience. We encourage you to apply for this role if you find it interesting, even if you do not meet all the requirements. This job is part of our ongoing effort to significantly expand all our technical teams, so please check our other advertised positions.

Responsibilities

  • Working on a range of problems in medical image analysis: image segmentation, classification, spatiotemporal analysis, object detection, registration, etc.
  • Experimenting with modern machine learning methods to solve major challenges. The work will focus on techniques which will be incorporated into our planning and registration software.
  • Writing and maintaining in-house machine learning packages, following best practices in software development and packaging.
  • Maintaining and improving data pipelines.
  • Collaborating closely with software engineers and the QA team to ensure the highest quality of developed solutions.
  • Managing projects from concept to delivery, adhering to design requirements and deadlines.
  • Keeping up to date with the latest developments in machine learning.
  • Presenting at internal meetings, as well as external meetups and conferences.

About you

As the ideal candidate you will have a sound understanding of modern machine learning techniques. You will be passionate about applying these techniques to solve real-world problems; rigorous when prototyping and experimenting; and able to express your solutions in high quality code. As a member of the Science team at Cydar Medical, you will be expected to work collaboratively, sharing your ideas with others and learning new techniques and skills.

Essential requirements:

  • experience using Python deep learning frameworks (TensorFlow, PyTorch, etc.)
  • proficiency in Python
  • experience applying deep learning methods to real-world problems
  • strong analytical and problem-solving skills
  • knowledge of good programming practices and software development principles
  • permission to work in the United Kingdom

Desired skills:

  • image/volume processing libraries, e.g. ITK, VTK, OpenCV, scikit-image
  • git or other version control systems
  • algorithm design and development

Working environment

Cydar is based in Barrington, just outside Cambridge. Our offices are located in a historic water mill with views over the surrounding countryside.

Due to the pandemic we are currently working in a fully distributed way. We have always given support for flexible working arrangements and this has enabled us to adapt well to the changes required this year. We will continue to offer flexible working arrangements once home working is no longer an imperative –arrangements for a balance of office- and home-based working at other times can be discussed.

Diversity

Cydar is an inclusive workplace and we positively welcome applications from all backgrounds. Applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, and other protected characteristics. We believe diversity drives innovation so we are building a culture where difference is valued.

 

All Applicants must have the eligibility to live and work in the UK.

 

Please note that we are not working with recruitment agencies for this position. Unsolicited CVs sent by agencies will not be opened or acknowledged, and will not imply any acceptance of terms.

 

 

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  • Location
    Cambridge, Cambridgeshire
  • Department
    Science
  • Employment Type
    Full-Time