Product Manager, Technology Strategy & Compute

Posted 16 Days Ago
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London, England
Mid level
Artificial Intelligence
The Role
The Product Manager will develop long-range compute plans, build financial models, and communicate strategies across Google to optimize compute resources for GDM's mission.
Summary Generated by Built In

Snapshot

This is a key strategic role for GDM and is part of the critical planning and delivery of the right technology capacities to deliver on our mission. This role is part of Google DeepMind’s (GDM) Technology Strategy team cutting across technical strategy in areas like compute, data, and Gemini. This role requires a unique combination and application of deep financial, business, technical, and organizational understanding. The role will navigate how GDM and wider Google maximally leverage our multi-year $XXB compute budget as it relates to the GDM Mission, Gemini, and wider Google impact.

About us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The roleResponsibilities:

  • Long-Range Compute Planning:
    • Develop and maintain a comprehensive long-range compute plan that anticipates future compute needs and aligns with Google's strategic objectives.
    • Work with Google teams to continuously monitor and analyse actual compute usage patterns.
    • Incorporate the latest technological advancements and ground truth data into the compute planning models.
    • Identify opportunities to improve the accuracy and efficiency of our forecasting and planning processes.
  • Financial Modeling & Analysis:
    • Build detailed financial models to evaluate the costs and benefits of different compute options.
    • Conduct sensitivity analyses and scenario planning to assess the impact of various factors on compute costs and Google’s strategic flexibility.
    • Build and maintain high level financial models of main industry players.
    • Analyse the financial health and strategies of key industry players and competitors
  • Product Narrative & Communication:
    • Develop a compelling narrative around the compute planning model..
    • Communicate changes to the model and their rationale to stakeholders across Google, ensuring transparency and buy-in.
    • Create presentations, reports, and other materials to effectively communicate the model and its implications.

About you

In order to set you up for success at Google DeepMind, we look for the following skills and experience:

  • Bachelor's degree in a quantitative field (e.g., finance, economics, engineering, computer science).
  • 3+ years of experience in financial modeling and analysis, preferably in an investment research, strategic consulting, or technology company setting or as a product manager in a go-to-market function.
  • Strong analytical and problem-solving skills with the ability to synthesise complex information and draw meaningful insights.
  • Excellent communication and presentation skills with the ability to effectively convey technical information to both technical and non-technical audiences.
  • Passion for AI and a strong understanding of the AI landscape.

Preferred Qualifications:

  • CFA, MBA or Master's degree in a relevant field.
  • Familiarity with markets for AI hardware and software technologies.
  • Experience with cloud computing platforms (e.g., Google Cloud, AWS, Azure).

We encourage applications from candidates with diverse backgrounds and experiences. If you have a strong analytical aptitude, a passion for understanding complex systems, and the ability to develop well-reasoned insights, even if your background doesn't perfectly align with the "traditional" qualifications, we encourage you to apply. In your cover letter, please highlight how your unique experiences and skills make you a strong candidate for this role, and feel free to include any relevant work samples (e.g., reports, analyses) that demonstrate your abilities.

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

 

Top Skills

AWS
Azure
Cloud Computing
Financial Modeling
GCP
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The Company
1,218 Employees
On-site Workplace
Year Founded: 2010

What We Do

We’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI).

Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges.

We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.

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