Research Engineer, Gemini Omni Data Infrastructure, DeepMind

On-site in London·Added yesterday (last checked 12 Nov)

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Our summary

Work mode: On-site, London
Experience: 2+ years

Skills

Nice to have

Requirements

What we're looking for

Bachelor’s degree or equivalent practical experience.
2 years of software development or ML research experience, or education equivalent credit (e.g., internships, student research, pre-graduate working experience).
Experience conducting research to solve problems in AI or ML.
Experience in implementing machine learning algorithms or techniques (e.g., basicautomatic differentiation) and in using machine learning frameworks (e.g., Jax, PyTorch, Triton).
Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
One or more scientific publication submission(s) for conferences, journals, or public repositories, including publications on machine learning or computational neuroscience.

Nice to have

Experience with distributed storage systems, relational databases, and schema or query design (e.g., PostgreSQL, Cloud Spanner, Bigtable, Cassandra, or DynamoDB).
Experience with large-scale data pipelines and distributed batch or streaming frameworks (e.g., Apache Beam, Spark, Dataflow, Ray, or Flink).
Prior experience building data infrastructure, pipelines, or tooling within an ML research environment.
Familiarity with a compiled systems/backend language (such as C++, Rust, Go, or Java) or media codecs (video, audio, image).

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 varied career pathways for those driven to achieve exceptional results through collective effort.

What you'll do

Write product or system development code.
Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.

Hiring process

4 steps3 interviewsa task to do6–8 weeks in all

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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.