AI/Machine Learning Engineer

1 week ago

London, Greater London, United Kingdom GlaxoSmithKline Full time
About the Role

We are seeking a highly skilled Machine Learning Engineer to join our Responsible AI team at GlaxoSmithKline. As a key member of our team, you will play a critical role in developing and implementing AI and machine learning solutions that drive business value and improve patient outcomes.

Key Responsibilities
  • Design and develop state-of-the-art machine learning models to address complex problems in AI ethics and safety, drug discovery, and biomedical data analysis.
  • Collaborate with cross-functional teams to integrate machine learning solutions into our software products and pipelines.
  • Contribute to research and development of new machine learning techniques and algorithms to improve the responsible use of AI in drug discovery and clinical applications.
  • Work closely with research scientists, senior leaders, and AI/ML engineers to implement our responsible AI strategy.
Requirements
  • Master's or Ph.D. degree in a quantitative or engineering discipline (e.g., computer science, computational biology, bioinformatics, engineering).
  • Advanced programming expertise in Python and experience with developing and delivering robust software solutions.
  • Knowledge of machine learning principles, state-of-the-art modeling approaches, and experience with major deep learning frameworks (e.g., PyTorch).
  • Knowledge of modern software engineering tools and best practices.
  • Proven ability to collaborate with colleagues of various backgrounds and levels of seniority.
Preferred Qualifications
  • Experience building and evaluating large language models (LLMs) and LLM-based applications.
  • Experience working with biomedical data (e.g., genomics, transcriptomics, proteomics, electronic health records, clinical images).
  • Research experience (Ph.D., Master's project, internship at research organization).
  • Contributions to relevant open-source projects.
  • A background or interest in drug discovery, biology, medicine, or ethics.

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