Director of Product Management, Gemini Code Lead

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Mountain View, CA, USA
In-Office
Artificial Intelligence
The Role
Director of Product Management, Gemini Code LeadMountain View, California

Snapshot 

 

The code PM will be responsible for setting and driving a strategy for Gemini’s coding ability, with the goal of making Gemini the best models for developers both within and outside Google.


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 role

 

Key responsibilities

  • Lead the product strategy for Gemini’s coding abilities, by creating a cohesive roadmap for key use cases and product priorities

  • Lead Gemini’s strategy in the development of an agent to support developers in their critical workflows

  • Develop a strong set of evaluations for key use cases and a data strategy that encompasses quality, style, and collection approaches

  • Drive critical model improvements for the key use cases, in partnership with the right surfaces and UX to enable Gemini adoption.

  • Partner with the broader ecosystem to identify new features and capabilities for AI-powered code

  • Look ahead to new & emerging coding use cases, and develop solutions for these efforts

About you

 

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


  • BSc or MSc in Computer Science or equivalent technical field

  • At least 10 years of PM experience (or equivalent sets of landings)

In addition, the following would be an advantage: 

  • Previous experience as a developer and/or personal involvement in developer communities 

  • Track record of driving launches through complex stakeholder management.

  • Ability to deliver products that drive customer success and market leadership.

  • Previous experience working on ML/AI products.

The US base salary range for this full-time position is between $253,000 - $379,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Application deadline: 12pm GMT Thursday 20 February 2025





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.



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The Company
1,218 Employees
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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