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Manager, Applied AI Engineering

On-site in London·Added 1 month ago

Google

168 open roles

Overview

Requirements

  • Work on-site in London

    No relocation package mentioned.

  • Have 8+ years of experience

    Director-level role.

Skills

Nice to have

Requirements

Minimum qualifications:
  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
  • 8 years of software development experience, including system design, data structures, and algorithms.
  • 7 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • 5 years of experience in a technical leadership role; overseeing projects, with 5 years of experience in a people management, supervision/team leadership role.

Preferred qualifications:
  • 5 years of experience with one or more of the following: media generation, reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  • Experience with generative AI research or applications.
  • Experience evaluating model performance, analyzing results, and implementing improvements.
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.
  • Experience in developing and shipping software products rapidly.
  • Contributions to open-source projects.

The role

In this role, you will lead the development and deployment of novel applications, leveraging Google's generative AI models. This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google and Google customers. You will be instrumental in translating AI research into real-world products, and demonstrating the capabilities of latest generation models. You will be building and shipping software, and leading engineering teams, ideally with some experience in early-stage environments, where you may have contributed to scaling products from initial concept to production. You will drive product and business impact, and develop strong relationships with research teams. You will be a passionate machine learning engineering leader with a drive to build innovative products and a desire to work at the forefront of AI.

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.
Responsibilities
  • Lead a team in the design, development, and deployment of scalable generative AI applications and advocating industry best practices.
  • Lead the team through the rapid development of new features, iterating based on evaluation results while mentoring members to cultivate a collaborative and high-performing environment.
  • Collaborate with researchers and product managers to translate research advancements into tangible product features.
  • Oversee the optimization of software performance and ensure the reliability of deployed applications.
  • Lead the architecture and development of new products and features from 0 to 1.

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
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