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AI/Machine Learning Engineer
2 months ago
We are seeking a highly skilled AI/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 solutions that drive innovation and improve patient outcomes.
Key Responsibilities- Apply state-of-the-art machine learning methods to problems in AI ethics and safety, drug discovery, and clinical applications.
- Support cross-functional teams to turn applied AI research into reliable and safe machine learning pipelines and software products.
- Contribute to machine learning research on the responsible use of AI in drug discovery and clinical applications.
- Collaborate with research scientists, senior leaders, and AI/ML engineers to implement GSK's responsible AI strategy.
- 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 ML engineer or data scientist.
- Demonstrated advanced programming expertise in Python and in developing and delivering robust software solutions.
- Knowledge of machine learning principles and state-of-the-art modeling approaches, and experience with at least one major deep learning framework (preferably PyTorch).
- Knowledge of modern software engineering tools and best practices.
- Keenness to learn fast in a new domain and to continuously develop your ML and software engineering skills.
- Proactive communication and problem-solving, and a proven ability to collaborate with colleagues of various backgrounds and levels of seniority.
- 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 (PhD, Master's project, internship at research organization).
- Contributions to relevant open-source projects.
- A background or interest in drug discovery, biology, medicine, or ethics.
