Applied Machine Learning Engineer

  • Dawson Hall - Charterhouse Square, London, United Kingdom
  • Full-time
  • Department: N/A
  • Office: London

Company Description

Genomics England successfully led the world-leading 100,000 Genomes Project, which compared and analysed individuals’ genetic codes to help diagnose, treat and prevent illness.

We are accelerating our impact, working with the NHS to further develop and embed genomic healthcare and research in Britain.  We work with patients, doctors, scientists, government and industry to improve genomic testing, and help researchers access the health data and technology they need to make new medical discoveries and create more effective, targeted medicines for everybody.

Job Description

Our Applied Machine Learning Engineer will solve complex predictive modelling challenges for improving health care and enabling biomedical research.

Through cross-disciplinary collaborations and agile practices, this role will drive different phases of the machine learning lifecycle at our company.

This will require designing, building and evaluating machine learning models with different types of large-scale, patient-derived data.

By bringing technical expertise and hands-on implementations, the Applied ML Engineer will help us create products that will transform health care in the UK and everywhere.

Other duties include:

  • Design, implement and evaluate ML models and software prototypes.
  • Apply technical expertise to generate insights, tools and applications using massive sets of biomedical data, including genomics and other health care datasets.
  • Actively collaborate with other data scientists, biomedical domain experts, product managers and other partners to develop ML-driven services and products.
  • Propose and engage in multiple team collaborations, including those with external partners, to help us deliver on our research and health care mission

 

We are looking for an individual with a passion for Machine Learning, experienced in a research/technical field designing, building and evaluating models with well-established ML frameworks, such as TensorFlow or PyTorch.

Solid theoretical understanding and practical experience of diverse machine learning approaches, including (but not limited) to deep learning.

Track record of cross-functional collaborations for developing ML applications, including the capacity to deliver production-level code.

Practical experience developing applications with AWS ML services and a solid understanding and skills in software development best practices (including Agile/Scrum, CI/CD) are highly desirable.

Qualifications

MSc. degree or equivalent practical experience in academic or commercial settings.

Additional Information

The successful candidate will receive a competitive salary and benefits package along with the opportunity of working and collaborating with the best researchers and bioinformaticians in the UK.

As part of our recruitment process, all successful candidates are subject to a Standard Disclosure and Barring Service (DBS) check.  We therefore require applicants to disclose any previous offences at point of application, as some unspent convictions may mean we are unable to proceed with your application due to the nature of our work in healthcare. 

Genomics England operate a blended working model, as we know our people appreciate the flexibility.  We expect most people to come into the office 2 times each month as a minimum. However, this will vary according to role and will be agreed with your team leader. For some people this is 1 day a quarter, for others it is several days a week.  There is no expectation that staff will return to the office full time unless they want to. The exception would be some of our roles that would require you to be on site full time e.g., lab teams, reception team. 

Our teams and squads have, and will continue to, reflect on what works best for them to work together successfully and have the freedom to design working patterns to suit, beyond the minimum. Our office locations at the moment are Cambridge and Farringdon (London) and in Summer 2022 we are relocating our London office location to Canary Wharf.  We will also be expanding our regional offices.   

Looking ahead to our move to Canary Wharf, we will be designing our new space with blended working in mind, and with the flexibility to adapt to changing work patterns. During the pandemic we will be following government advice on working from home guidance. 

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