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Tech Lead, Gemini Inference Performance, DeepMind

On-site in London·Added 10 days ago (last checked 15 Oct)

Google

249 open roles

Requirements

Minimum qualifications:
  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years of experience in a people management, supervision/team leadership role.
  • 5 years of experience in a technical leadership role and overseeing projects.

Preferred qualifications:
  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  • 5 years of experience working in a complex, matrixed organization.

The role

Artificial intelligence will be one of humanity's most transformative inventions. At Google 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 diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Responsibilities
  • Set the technical roadmap for a team of performance engineers, support and develop direct reports and drive prioritization across competing optimization opportunities - staying in the highest-leverage problems.
  • Leverage roofline analysis, hardware-level profiling, and systems analysis to identify and eliminate performance bottlenecks across ML frameworks, compilers, custom kernels, and serving infrastructure on hardware accelerators.
  • Apply a first-principles understanding of Transformer and Mixture-of-Experts model components to identify and prioritize opportunities to optimize their execution efficiency and memory footprint.
  • Collaborate with research teams early in the development lifecycle to evaluate inference implications, modeling how architectural choices impact latency, memory footprint, and serving costs.
  • Guide and contribute to the development of custom kernels and serving optimizations. Conduct deep performance profiling using hardware tracing tools to analyze accelerator utilization, memory bandwidth saturation, and interconnect latency across large-scale topologies.

Hiring process

4 steps3 interviewsa task to do6–8 weeks in all
  1. Apply online

  2. 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.

  3. 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.

  4. Project work

    In your own time · Not every role

    For some roles, a small project before interviews: a case study, writing or code samples.

  5. 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.

  6. 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.

About Google

Industry
Technology
Founded
1998
Employees
100,000+
Headquarters
Mountain View, USA
Website
google.com
All open roles at Google

Location

Google · London

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