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Salary
≈ $95k – $185k per year (Estimated)
Location
In office (London)
Seniority
Staff · 8+ years exp

Confirmed on the employer's own hiring board on Oct 28, 2026. First seen by Alion on Oct 26, 2026.

Overview
Company
Impact
Profile match
Google DeepMind is the artificial intelligence research and engineering division of Alphabet, formed in 2023 by merging the London laboratory founded in 2010 with the Google Brain team. It builds frontier foundation models such as the Gemini family, generative media systems including Veo and Imagen, and scientific tools like AlphaFold, whose protein structure predictions earned a share of the 2024 Nobel Prize in Chemistry. The unit pairs long-horizon research on reinforcement learning and general intelligence with product delivery across Google Search, Workspace, Android and Google Cloud.

About the job

Artificial intelligence will be one of humanity’s most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer varied learning opportunities and career pathways for those driven to achieve exceptional results through collective effort.

Responsibilities

  • Partner closely with product leadership, external parties (e.g., biosecurity organizations, research institutes, public health authorities) and internal cross-functional teams to navigate ambiguity, deeply understand real-world biological defense challenges, and define clear product requirements and software architecture.
  • Build robust data pipelines for complex biological datasets, implement scalable evaluation frameworks, and optimize model inference and serving infrastructure for production use.
  • Contribute extensively to the engineering and development of novel solutions from 0 to 1, utilizing internal platforms and tools to build reliable production applications, agents, and workflows powered by GDM foundation models.
  • Translate experimental research prototypes into maintainable software, sharing deployment telemetry, system performance constraints, and edge cases with core research teams to inform future model development.
  • Set software engineering best practices for applied GenAI systems, focusing on testing, system reliability, security, and maintainability across deployed tools.

Qualifications

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development.

Preferred qualifications:

  • Experience applying deep learning models to biological data (such as functional genomics or protein sequence data).
  • Experience working with life science data, such as in bioinformatics or health informatics.
  • Ability to identify, break down, and solve ambiguous and complex process and technical problems that span across many teams and organizations.
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