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Google DeepMind's Impact Accelerator is a team focused on catalysing AI breakthroughs through socially beneficial projects and partnerships, including building upon our work on AlphaFold. 

The Google DeepMind Institute (GDI) has a unique role in GDM, to develop solutions and resources built on GDM's technologies and expertise that extend the benefits to humanity. We are a path to real world impact, beyond Google products and services or making our research public. 

In this role you will work in a close-knit team of engineers to bring the benefits of GDM’s technologies to the APAC region.

Responsibilities range from keeping open access tools best in class by developing new features and libraries within production environments, to working in partnership with and advising external partner organisations.

• Lead and manage a team of Software and Research Engineers, working with the Impact Lead and GDI Engineering Lead to prioritise impact opportunities.

• Develop, maintain and extend AI deployment solutions in response to user feedback and strategic priorities, for example web services, open source software, and data access solutions.

• Apply your software engineering expertise to guide and advise external impact partners.

• Ensure a healthy team environment and develop the engineering talent on the team.

The role will suit candidates who enjoy applying state-of-the-art AI to important scientific and real-world problems for maximum impact for the wider community.

Software Engineers come from diverse backgrounds, sometimes with degrees in Computer Science and sometimes with extensive experience with real problems, or both. In order to set you up for success as an Engineering Lead at DeepMind, we look for the following skills and experience:

• A degree in computer science, electrical engineering or equivalent experience.

• 4 years of experience in a technical leadership role; overseeing projects, with 2 years of experience in a people management, supervision/team leadership role

• Proven experience in Python, C++, and interoperability between the two.

• Experience with concurrent and distributed software algorithms and architectures.

• Experience with deployment in production environments.

• Understanding of nature of AI development and deployment and what technology can and cannot do, beyond GenAI.

In addition, the following would be an advantage: 

• Experience using GCP and other cloud solutions.

• Familiarity with modern hardware accelerators (GPU/TPY).

• A deep interest in AI and how it can make a difference in the world.