AIML Engineer, AI for Science

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.

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, leveraging high performance computing and the biomedical data sources available at GSK.

The AI4S team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term and 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.

• 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.

• 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.

• 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).

If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $160,050 to $266,750. The US salary ranges take into account a number of factors including work location within the US market, the candidate's skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, paid caregiver/parental and medical leave.

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.