Senior Applied AI Engineer at GSK delivering high-impact AI/ML solutions aligned with R&D priorities. Collaborating with cross-functional teams to build and deploy machine learning models for drug discovery.
Responsibilities
As a Senior Applied AI Engineer, you will be embedded within cross-functional teams to deliver practical, high-impact AI/ML solutions aligned with GSK’s R&D and business priorities.
Partner closely with scientists, product teams, and domain experts to design, build, and deploy machine learning models and AI-powered tools that accelerate drug discovery, improve decision-making, and enable responsible use of AI across the enterprise.
Evaluate use-case feasibility, prototype solutions rapidly, architect model integrations, and transfer knowledge so that partner teams can operate independently.
Contribute to the development of reusable patterns, baseline models, and tested pipelines for common AI/ML tasks within GSK’s approved.
Requirements
Bachelor’s degree in Computer Science, Machine Learning, Computational Biology, Bioinformatics, Statistics, Engineering, or a related quantitative discipline; OR equivalent professional experience as a software/ML engineer.
3+ years of professional experience developing and deploying machine learning models (with a Bachelor’s); 2+ years with a Master’s or PhD.
Expertise in Python, including ML/data science libraries (PyTorch, TensorFlow, JAX, scikit-learn, pandas, numpy).
Experience with cloud platforms (GCP, AWS, or Azure) and containerization (Docker, Kubernetes).
Strong understanding of ML fundamentals: supervised/unsupervised learning, deep learning, model evaluation, feature engineering, and experiment tracking.
Experience working in cross-functional teams and communicating technical concepts to non-technical stakeholders.
Experience working in healthcare, pharma, or biological domains.
Benefits
health care and other insurance benefits (for employee and family)
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