Technical Recruitment, Business Development, Data Conversion System (DCS), Machine learning techniques, Management
This role sits within Google DeepMind's Data Team. The team is responsible for the sourcing, acquisition and management of data to accelerate our research goals. This role will focus on working with our range of external data acquisition partners to ensure that industry best practice and contractual obligations are governed in an ambiguous and evolving industry.
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.
We constantly iterate on our workplace experience with the goal of ensuring it encourages a balanced life. From excellent office facilities through to extensive manager support, we strive to support our people and their needs as effectively as possible.
Our list of benefits is extensive, and we’re happy to discuss this further throughout the interview process!
The Role
As a Technical Program Manager in this team you will play a key role in working with our partners to ensure that ethical, legal and secure best practices are established and adhered to.
Key responsibilities:
About You
We’re looking for someone who is passionate about collaborating across the AI industry to build a bold and responsible future.
In order to set you up for success as a Technical Program Manager at Google DeepMind, we look for the following skills and experience:
Google DeepMind, officially known as DeepMind Technologies Limited, is an artificial intelligence (AI) research company that serves as a subsidiary of Google. It was founded in the United Kingdom in 2010 by Demis Hassabis, Shane Legg, and Mustafa Suleyman. DeepMind gained significant attention for its advancements in machine learning and AI technologies.
Ann Arbor, MI, USA; Austin, TX, USA; Cambridge, MA, USA; Chapel Hill, NC, USA; Chicago, IL, USA; Irvine, CA, USA; Kirkland, WA, USA; Los Angeles, CA, USA; Madison, WI, USA; Mountain View, CA, USA; New York, NY, USA; Palo Alto, CA, USA; Pittsburgh, PA, USA; Princeton, NJ, USA; San Bruno, CA, USA; San Francisco, CA, USA; Seattle, WA, USA; Sunnyvale, CA, USA; Washington D.C., DC, USA
0-2 year