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Machine Learning Engineering Lead, London


Job details
  • TN United Kingdom
  • London
  • 1 week ago

Social network you want to login/join with:Machine Learning Engineering Lead, LondonClient: GSKLocation: London, United KingdomEU work permit required: YesJob Reference: 9597a69d54c8Job Views: 5Posted: 11.02.2025Expiry Date: 28.03.2025Job Description:

Job description

Ensure you read the information regarding this opportunity thoroughly before making an application.Site Name:

London The Stanley BuildingPosted Date:

Sep 5 2024

At GSK we see a world in which advanced applications of machine learning and AI will allow us to develop novel therapies to existing diseases and to quickly respond to emerging or changing diseases with personalized treatments, driving better outcomes at reduced cost with fewer side effects. It is an ambitious vision that will require the development of products and solutions at the cutting edge of machine learning and AI. If that excites you, we'd love to chat.The AI/ML RNA Therapeutics team applies machine learning and AI methods to fundamental problems in RNA biology and biochemistry domain in order to accelerate the discovery and development of novel RNA therapeutics. Improved target identification and therapeutic design in this space has the potential to be transformative, empowering scientists to make better and faster data-driven decisions about potential therapeutics.We are looking for a

Lead of ML Engineering – RNA Therapeutics . This is a technical management track role with responsibility for direct reports. The candidate should be comfortable being accountable for setting the direction, standards and culture of a machine learning engineering sub-team, with demonstrable expertise across machine learning, software engineering and biology. Equally important will be excellent communication, interpersonal and organisational skills, and the ability to represent and transmit the values and principles of our organisation.The AI/ML team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career and development from day one.In this role you willLead a machine learning engineering team specialising in fundamental problems in RNA biology and chemistryManage complex, multi-quarter, cross-functional projectsBe a standard bearer for data science and software engineering best practices within the organisationDevelop plans to meet requirements, organize a team capable of executing the plans, and lead and track delivery.Maintain a safe and inclusive team environment in which people thriveOperate in a transparent way, communicating clearly and accurately to leadership and the broader organizationDevelop a high-performing team through coaching, feedback and ensuring opportunities for growthWhy you?Qualifications & Skills:We are looking for professionals with these required skills to achieve our goals:Graduate studies in Computer Science or Applied Math, undergraduate studies in Computer Science and relevant graduate studies in the life sciences with a focus on AI/ML techniques, or undergraduate studies in Computer Science and equivalent work history. Candidates with graduate studies in CS and biological sciences or equivalent work history will be highly competitiveTrack record as an independent contributor capable of end-to-end development of ML-powered products for biological or pharmaceutical applicationsAdvanced Python programming skills and a track record of delivering robust software solutions3+ years experience in a technical lead or engineering manager role with direct reports5+ years experience of professional software development practices: code standards, code review, version control, CI/CD, testing, documentation, Agile, with the ability to mentor others in these practicesProficiency with standard deep learning algorithms and model architectures, including sequence or graph based methodsIn depth knowledge in machine learning best practices, scalable training and deploymentPreferred Qualifications & Skills:If you have the following characteristics, it would be a plus:PhD in Machine Learning or Computer ScienceExperience working with large ML-powered systems in a production settingKnowledge in molecular biology, disease biology and/or biochemistryPeer reviewed publications in major AI conferencesClosing Date for Applications: Thursday 29th August 2024 (COB)Please take a copy of the Job Description, as this will not be available post closure of the advert.When applying for this role, please use the ‘cover letter’ of the online application or your CV to describe how you meet the competencies for this role, as outlined in the job requirements above. The information that you have provided in your cover letter and CV will be used to assess your application.Why GSK?Uniting science, technology and talent to get ahead of disease together.GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.

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