Software Engineer, Bioresilience, DeepMind

On-site in London·Added today (last checked 26 Oct)

Google

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Requirements

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.

The role

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.

Hiring process

4 steps3 interviewsa task to do6–8 weeks in all

Apply online
Assessments
Online test · Not every role
You may be asked to take the Google Hiring Assessment (workstyle skills) and, for some roles, role-related assessments such as a coding exercise.
Recruiter conversations
With a recruiter · Phone call · 1–2 sessions
One or two shorter conversations assessing key skills, sharing information about the organisation and team, and asking about your preferences such as location.
Project work
In your own time · Not every role
For some roles, a small project before interviews: a case study, writing or code samples.
Interviews
With a rotating cast of Googlers
A panel of structured interviews, over video or in person, with a rotating cast of Googlers; open-ended role-related questions scored against the same rubric for every candidate, no brainteasers.
Decision and offer · With a recruiter

Structured interviews: every candidate for a role is scored against the same rubric; no brainteasers.
AI tools are not permitted during interviews.
For some roles, pre-selected interviews happen virtually before final interviews onsite.