AI/ML Engineer II

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 drugs, 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 would love to chat. We are looking for an AI/ML Engineer to help us make this vision a reality.

Competitive candidates are outstanding engineers with a track record in developing SOTA deep learning models for solving challenging real world scientific problems and production grade AI-powered software solutions. Our team focuses on the discovery of preclinical digital biomarkers that translate robustly to clinical outcomes. An important outcome of our work is that, while enabling deeper insights into the effects and mechanisms of action of treatments, it also helps to advance the 3Rs framework, a set of principles that guide the ethical and humane use of animals in scientific research.

In this role you will:

• Convert vaguely described biological/drug discovery challenges into well-defined machine learning problems, particularly in the computer vision domain (both images and video).
• Execute and deliver full AI/ML driven solution from sourcing training data, design and implementing SOTA machine learning models, testing, benchmarking, and product driven research for model performance improvement, to shipping stable, tested, performant code and services in an agile environment.
• Engage with a diverse group of research scientists to help solve complex problems in the preclinical domain.

Qualifications & Skills:

We are looking for professionals with these required skills to achieve our goals:

• A degree in a quantitative or engineering discipline (e.g., computer science, computational biology, bioinformatics, engineering, among others); OR equivalent work experience as a professional AI/ML engineer.
• Experienced in developing deep learning models for solving real world scientific problems.
• An outstanding software engineer and machine learning engineer.
• Demonstrable expertise and depth in at least one area and breadth across your expertise.
• Experienced/accomplished in software engineering with advanced skills and expertise in best practices for Pythonic programming.
• Proficiency with standard deep learning algorithms and model architectures.
• Familiarity with current deep learning literature and math of machine learning.
• In-depth knowledge in machine learning best practices, scalable training and deployment, model introspection and evaluation.
• Experience in deep learning for computer vision, including but not limited to image segmentation and object detection.
• Advanced level in PyTorch or Tensorflow.
• Experience with devop stacks: version control, CI/CD, containerization, etc.
• A thorough understanding of security and privacy best practices as relates to data and code.

Preferred Qualifications & Skills:

If you have the following characteristics, it would be a plus:

• Track record of contributing to open-source projects, or evidence of working collaboratively on codebases.
• Mentality of commit early and often, metrics before models, and shipping high quality production code.
• Experience with video analysis and tracking.
• Experience/familiar with different modules of an ML product interacting with each other asynchronously.
• Knowledge in disease biology, molecular biology and biochemistry.
• Experience with biological data (e.g., genomics, transcriptomics, epigenomics, proteomics, etc.).

Closing Date for Applications: Thursday 10th July 2025 (COB)

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.