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.
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
- 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).
Salary
Germany Salary Range / Gehaltsbandbreiten Deutschland: EUR 84,000 to EUR 140,000. For positions covered by collective bargaining, employment conditions and remuneration are determined by the applicable collective agreements for the chemical industry as well as internal policies. More detailed information on compensation will be provided during the recruitment process. Depending on the role and internal policies, the position may also be eligible for a bonus (if applicable and based on defined, non-discretionary criteria) and/or awards for exceptional performance (granted at the employer’s discretion). All benefits arising from the applicable collective bargaining agreement, such as holiday allowance and additional paid time off, will be provided in full, in accordance with that agreement and German law. Other benefits may also be offered, which may include health & wellbeing benefits, pension plan and paid parental leave & care of family member leave.
Equal Opportunity
GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.
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