AI/ML Engineer, GSK
2-5 days a week in office
Building a cutting-edge digital and tech team.
Job no longer available
Building a cutting-edge digital and tech team.
1001+ employees
Job no longer available
2-5 days a week in office
1001+ employees
Company mission
At GSK, we use technology to deliver what matters most, better and faster. Whether it’s life-saving medicines or life-enhancing products, Tech at GSK helps scale and accelerate our expertise.
Role
Who you are
- A minimum of a master’s degree in computer science, applied math, statistics, physics, systems biology, computational biology, bioinformatics, or related field
- Experience in Python programming and knowledge in machine learning and statistics
- Demonstrated proficiency working with biological/healthcare data in an academic or professional setting
- Familiarity with at least one Deep Learning framework such as TensorFlow, Keras or PyTorch
- Proven ability to solve complex problems using creative approaches, state-of-the-art tools, and best engineering practices
- Ability to work both autonomously and collaboratively on complex projects
Desirable
- A PhD in computer science, applied math, statistics, physics, systems biology, computational biology, bioinformatics, or related field
- Academic or industry experience in the biomedical sciences
- Expertise developing machine learning models within the PyTorch framework
- Experience with theory & applications in software engineering; training and operating algorithms at scale; production deployment of ML services
- Ability to digest, synthesize, and implement innovative methods from scientific literature
What the job involves
- By actively engaging with the machine learning community and publishing our research, code and models built on public data, the AI/ML group operates at the cutting-edge of machine learning research
- To help us, we seek a passionate Machine Learning Engineer who wishes to turn their talents to the healthcare sector
- You will be working with other engineers on building products to support multiple large-scale projects within AI/ML
- In addition, the engineer will learn about the pharmaceutical industry and software engineering and translate their research into tools that aid discovery and development of transformational medicines
- You will have access to outstanding experts in biology, chemistry, (software) engineering, data science and machine learning; unrivalled data sources and GSK’s state-of-the-art laboratory and compute infrastructure to help you develop and validate your machine learning research
- Design and implement novel scientific approaches to uncover and explain key relationships within a multitude of biological data types
- Leverage data and insights to produce robust, explainable, and accurate predictions across a variety of key biological and clinical tasks
- Connect and collaborate with subject matter experts in biology, genomics, and medicine
- Identify opportunities to apply the latest advancements in Machine Learning and Artificial Intelligence to build, test, and validate predictive models
- Develop and embed automated processes for predictive model validation, deployment, and implementation
- Deploy your algorithms to production to identify actionable insights from large databases
Application process
- Closing Date for Applications: Wednesday 11th September 2024 (COB)
Salary benchmarks
Our take
GSK Tech is set to build a suite of next-generation platforms for data- and prediction-driven drug discovery in support of GSK's Research and AI/ML organizations, and an industry-leading data engineering function in support of AI/ML and Genomic Sciences.
GSK’s ambitions go far past the data lake: they’re building a comprehensive data and machine learning ecosystem that can speak to the customers in their own scientific and technical language and semantics. Enabled by GSK Knowledge Graph, powered by machine learning, and underpinned by natural language processing, GSK's vision is for accessibility to data (and, importantly, the knowledge it represents). GSK wants to increase this tenfold, taking mere moments to find, access, and integrate the right information.
The creation of GSK Tech shows GSK's commitment to making a major investment in changing how we think about data in the research space, and levelling up the data experience for GSK's researchers, scientists, computational scientists, AI/ML Engineers, and ultimately decision-makers. As of 2024, GSK is putting more energy into its Cyber Security features, thus widening its market reach.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Company benefits
- An annual bonus based on company performance
- Access to healthcare and wellbeing programmes, pension plan membership, savings programmes, time off and childcare support
- Employee recognition programmes which reward exceptional achievements
- Long term incentives through share ownership link your rewards to our longer term performance
- Coaching, mentoring and formal training programmes
- Plenty of opportunities for open conversations with people who can help to shape your career
- A range of health and wellbeing programmes and support services to help employees understand how to feel healthier, happier and more energised at work and at home
Company HQ
Brentford, UK
Leadership
Luke Miels
(CEO)Luke became CEO on Jan 1, 2026, after serving as CEO designate since Sept 2025. He joined GSK in 2017 as Chief Commercial Officer, responsible for our commercial portfolio of medicines and vaccines.
Shobie Ramakrishnan
(Chief Digital and Technology Officer)Has a broad experience in biotech and hi-tech companies. Has led Digital and Technology for GSK’s Global Commercial organisation, transforming the company’s capabilities in digital, data & analytics.
Michael Elmore
(SVP & Global Chief Information Security Officer)Experienced in building and leading tech teams across cyber security, IT infrastructure, application development, and more. A trusted advisor to VCs and startups focusing on cybersecurity advancements.
Shubha Chaudhari
(SVP, Development Digital & Tech)Previously worked at Novartis in several roles, including Head of Clinical Informatics, Global Head of Development Informatics, and Head of Digital Transformation.
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