Bioresilience AI Engineer for Global Biosecurity

Google LLC; Greater London; On-site; GBP 120,000 - 160,000; Full time

Job summary

Google DeepMind in London is seeking a Research Engineer for the Bioresilience initiative within the DeepMind Impact Accelerator. You will build and deploy novel applications leveraging frontier AI and GenAI tools to address global biosecurity challenges.

The role requires domain expertise in life sciences or computational biology, strong software engineering, and the ability to translate biological concepts into scalable computational workflows and evaluation benchmarks.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.

Responsibilities

• Partner with product leadership and cross-functional teams to navigate ambiguity and define technical architectures across Bioresilience workstreams.
• Curate specialized biological datasets, design domain evaluations, and fine-tune to maximize model performance on biological tasks.
• Engineer 0-to-1 solutions and workflows using internal platforms and foundation models.
• Synthesize partner insights and deployment signals to inform frontier model development and safety guardrails.
• Advocate safe GenAI deployment practices in bioresilience and demonstrate capabilities end-to-end.

Skills

Software development experience

Software testing/maintenance/launching

Education

Bachelor's degree or equivalent practical experience

Job description

Google DeepMind in London is seeking a Research Engineer for the Bioresilience initiative within the DeepMind Impact Accelerator. You will build and deploy novel applications leveraging frontier AI and GenAI tools to address global biosecurity challenges.

The role requires domain expertise in life sciences or computational biology, strong software engineering, and the ability to translate biological concepts into scalable computational workflows and evaluation benchmarks.