Senior Director of AI Systems
£26.8 - £33.6 per hourEstimated
Full-time
Senior Director - Biomedical Foundation Models
London
The Senior Director, AI Systems will be responsible for building the technical foundations required to deploy biomedical foundation models at scale. The mandate includes establishing engineering standards, leading model architecture decisions, guiding pre-training and fine-tuning strategies, and ensuring that multimodal AI systems are designed for production deployment rather than isolated research outputs.
The position requires a leader who can balance technical ambition with practical delivery: someone who understands what foundation models can enable, how to build them responsibly, and how to align AI systems development with the scientific and commercial priorities of a global pharmaceutical organisation.
Key Responsibilities
Essential experience includes:
Strongly preferred experience includes:
The role offers the chance to influence how biomedical AI is developed, scaled, and embedded across a major R&D environment - not as a theoretical capability, but as a practical engine for scientific impact.
To express interest or recommend a suitable candidate, please contact us confidentially.
Keywords: AI / ML / Machine learning / artificial intelligence / foundation models / genomics foundation models / self-supervised learning / representation learning / patient representation learning / perturbation modelling / leader / leadership / strategy / strategic / techbio / biotech / biology / biological / biotechnology
London
The Senior Director, AI Systems will be responsible for building the technical foundations required to deploy biomedical foundation models at scale. The mandate includes establishing engineering standards, leading model architecture decisions, guiding pre-training and fine-tuning strategies, and ensuring that multimodal AI systems are designed for production deployment rather than isolated research outputs.
The position requires a leader who can balance technical ambition with practical delivery: someone who understands what foundation models can enable, how to build them responsibly, and how to align AI systems development with the scientific and commercial priorities of a global pharmaceutical organisation.
Key Responsibilities
- Lead and develop a team of AI Scientists and ML Engineers focused on biomedical foundation model development.
- Set the technical vision and engineering standards for large-scale AI systems across multimodal biomedical data.
- Oversee model architecture, pre-training, fine-tuning, multimodal fusion, validation, deployment, and production readiness.
- Partner with Applied AI, Analytics, AI Enablement, and R&D stakeholders to ensure models are aligned with drug discovery priorities.
- Build a culture of engineering excellence, technical rigour, and scalable delivery.
- Translate advances in AI research into practical, production-grade systems.
- Provide senior technical leadership across stakeholders, budgets, priorities, and organisational decision-making.
- Support the strategic adoption of AI across discovery, translational research, and related biomedical workflows.
Essential experience includes:
- Building and deploying large-scale ML systems or foundation models in production.
- Leading teams of ML Engineers, AI Scientists, or AI Researchers.
- Strong knowledge of foundation model architectures, including pre-training, fine-tuning, multimodal modelling, and deployment at scale.
- Experience setting engineering standards and production-quality expectations.
- Exposure to pharmaceutical R&D or drug discovery workflows.
- Senior leadership experience, including team growth, budget ownership, and stakeholder management.
- UK-based location or willingness to relocate to London.
Strongly preferred experience includes:
- Work with multimodal biomedical data such as medical imaging, omics, EHRs, or related datasets.
- Experience bridging AI research and production engineering.
- Familiarity with target identification, patient stratification, translational research, or clinical development timelines.
The role offers the chance to influence how biomedical AI is developed, scaled, and embedded across a major R&D environment - not as a theoretical capability, but as a practical engine for scientific impact.
To express interest or recommend a suitable candidate, please contact us confidentially.
Keywords: AI / ML / Machine learning / artificial intelligence / foundation models / genomics foundation models / self-supervised learning / representation learning / patient representation learning / perturbation modelling / leader / leadership / strategy / strategic / techbio / biotech / biology / biological / biotechnology
Vacancy posted 6 days ago
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