About the Role (Director & Group Head, AI Systems & Scale)
Drive the design and deployment of next-generation AI systems to accelerate drug discovery. Lead engineering teams, define scalable architectures, and ensure AI solutions are robust, governed, and impactful.
Key Responsibilities
- Define and lead the multi-year roadmap for scalable AI systems, platforms, and agentic architectures.
- Lead and scale multidisciplinary teams delivering production-grade AI systems.
- Establish reference architectures for agentic systems (orchestration, retrieval, memory, human-in-the-loop).
- Build and standardize enterprise agentic platforms with reusable components, workflows, and evaluation frameworks.
- Define and enforce MLOps and LLMOps standards.
- Own agent quality and safety engineering (guardrails, policy enforcement, failure detection).
- Drive scalable deployment strategies (performance, reliability, cost efficiency, multi-tenant architecture).
- Define metrics linking system effectiveness to scientific outcomes.
- Partner with data/security/platform teams for governance, compliance, and responsible data usage.
- Manage portfolio priorities and reduce duplication.
Essential Requirements
- 10+ years leading innovation/development/deployment/support of ML solutions.
- Experience leading ML capability development across drug discovery domains.
- ML expertise in computational chemistry and/or protein modeling.
- Large model training expertise (HPC, cloud, distributed systems).
- Passion for biomedical sciences and therapeutic discovery.
- Ability to explain complex ML to technical and non-technical stakeholders.
- Python and deep learning framework proficiency; version control experience.
- Ability to manage complexity and deliver in matrixed environments.
Desirable Requirements
- Enterprise-scale agentic platform experience (orchestration, memory, retrieval).
- ML Ops and large-scale deployment with monitoring and drift detection.