Remote Type: Hybrid (Remote & On-site)
Locations: UK - Kings Cross - London, Heidelberg, Switzerland - Zug
Time Type: Full time
Posted On: Posted 6 Days Ago
Job Requisition ID: 435678
At GSK, we see a world where advanced applications of Machine Learning and AI enable us to develop transformational medicines that drive better outcomes for patients at reduced cost and with fewer side effects. AI will also play a role in how we diagnose and use medicines to enable everyone to do more, feel better, and live longer. It is an ambitious vision that will require the development of products at the cutting edge of Machine Learning and AI.
About the Role
To strengthen our AI for Science (AI4S) team, we are looking for AI/ML Engineers with a track record in developing and validating machine learning models for real-world scientific problems. You will drive the development of AI models and agentic systems — researching, designing, implementing, and delivering solutions across a range of scientific tasks, including open-ended research questions, leveraging high-performance computing and the vast biomedical data sources available at GSK.
Team Culture
The AI4S team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we are motivated to make this a great place to work. Our leaders will be committed to your career and development from day one. We strongly encourage applications from people with diverse and underrepresented backgrounds and perspectives.
In this role you will
- Design and implement AI/ML-driven solutions throughout the entire model development life cycle.
- Research and develop state‑of‑the‑art machine learning models and agentic systems to solve a variety of scientific tasks.
- Deliver robust, tested, and high-performance code in an agile environment.
- Liaise with experts in biology, medicine and experimentation to ensure optimal data collection and processing for machine learning models.
Why you?
Qualifications & Skills:
- Bachelor’s, Master’s or Doctorate degree in a quantitative or engineering discipline (computer science, computational biology, bioinformatics, engineering, among others); OR equivalent work experience delivering state-of-the-art AI/ML solutions.
- Experience with at least one major deep learning framework (PyTorch, JAX, TensorFlow).
- Familiarity with machine learning literature and state-of-the-art approaches.
- Experience developing and delivering robust software solutions, including demonstrated advanced programming expertise in Python.
- Experience in software engineering and machine learning best practices, including version control, continuous integration (CI) and continuous development (CD), containerization, and shell scripting.
- Fluency in English.
Preferred Qualifications
If you have the following characteristics, it would be a plus:
- Experience in design, development and deployment of commercial AI/ML software.
- Experience with Large Language Models (LLMs) and Agentic AI (e.g., tool use, multi-agent orchestration, deployment and evaluation).
- Contributions to relevant open-source projects.
- Relevant scientific publications in AI/ML (e.g., NeurIPS, ICML, ICLR, AAAI), computational biology or bioinformatics venues.
- Knowledge of or interest in disease biology, molecular biology and medicine.
- Experience working with biomedical data (e.g., genomics, transcriptomics, proteomics, electronic health records, clinical images).
Please take a copy of the Job Description, as this will not be available post closure of the advert.
Ai/Ml Engineer employer: GlaxoSmithKline plc
GSK is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for professionals seeking to make a meaningful impact in the biopharma industry. With a commitment to employee growth through continuous learning opportunities and a flexible hybrid working model, GSK empowers its workforce to thrive while contributing to groundbreaking advancements in healthcare. Located in vibrant London, employees benefit from a dynamic work environment that prioritises ambition for patients and accountability for results.