Machine Learning Engineer

Machine Learning Engineer

About Us:

At Sensyne Health we combine technology and ethically sourced patient data to help people everywhere get better care. To do this, we have created a unique partnership with the NHS that delivers a return to our partner Trusts and unlocks the value of clinical data for research while safeguarding patient privacy. Alongside this, we develop clinically validated software applications that create clinician and patient benefit while providing highly curated data. Our products include vital-signs monitoring in hospitals and patient-to-clinician apps to support self-care and remote monitoring of gestational diabetes and chronic diseases such as COPD and heart failure.

We use our proprietary clinical AI technology to analyse ethically sourced, clinically curated, anonymised patient data to solve serious unmet medical needs across a wide range of therapeutic areas, enabling a new approach to clinical trial design, drug discovery, development, and post-marketing surveillance.

The Team:

We are a young team looking for an exceptional Machine Learning Engineer who is keen on applying state-of-the-art ML technologies to medical data. You will help us to deliver on one of our biggest, and most transformational projects yet.

Working to an agile methodology, and centred on data-efficient machine learning (ML) algorithms, we are building world leading data platforms and delivering on Sensyne’s mission to accelerate medical research and improve patient care.

The nature of our team is collaborative with an emphasis on genuine passion for healthcare. The roles are research and development based with high potential for professional growth, support towards our business goal and ongoing contribution to the development of healthcare.

Responsibilities:

  • Design and implement internal- and external-facing clinical Machine Learning (ML) or analytics applications at scale, e.g. microservices, data analysis applications, machine learning pipelines
  • Collaborate with, learn from, and support a diverse and cross-functional team, including data scientists, research scientists and software engineers
  • Design and implement a robust model training pipelines and infrastructure to support continuous delivery of ML applications
  • Mentor and support other engineers to improve coding practices and delivery principles
Essential:
  • Substantial previous experience in designing, developing and deploying production-grade applications
  • A track record of architecting clean abstractions, driving technical decision-making, and setting priorities in collaboration with external and internal stakeholders
  • Strong software development background with Python and other languages, and willingness to pick up new languages or technologies as needed
  • Hands-on experience using one of the following deep learning libraries: Tensorflow, PyTorch or similar
  • Valuing well-documented, clean, and tested code
  • Experience with continuous integration (e.g. CircleCI, GitlabCI, Github Actions)
  • Mastery of source control and code versioning tools such as Git and Github
  • Packaging and deploying applications using Docker, Kubernetes, etc.
  • Experience as a developer in an agile software development team
  • Can-do-attitude, keen on taking ownership and working with the team on solving engineering challenges.
Desirable:
  • Substantial experience with a cloud environment and provisioning resources for ML training/deployment (desirable Azure ML experience)
  • Experience of analysing clinical/healthcare data
  • Previous experience in a research environment
  • Company share option scheme
  • 5% employer matched salary sacrifice Pension scheme
  • Life Assurance & Income protection
  • A range of health, wealth and lifestyle benefit plans including BUPA, Gym and holiday trade options
  • Electric Vehicles & Cycle to work schemes
  • Proactive career development planning
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