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.Snapshot This role sits within the Reward & Recognition team; a current team of three based in London, embedded within our wider People & Culture team. You will be managed by the Lead, and collaborate closely with two other Partners.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 You’ll have responsibility for delivering processes and programs in North America, with a focus of working closely with our business leaders and talent acquisition teams. Key responsibilities
Provide advice and counsel to the Talent Acquisition team and hiring managers through the offer negotiation process.
Work with compensation metrics, reports, and tools to inform compensation decisions and forecast, report, and/or analyse compensation outcomes.
Communicate effectively with senior leaders and people & culture teams to provide insights to enable insights-led business decisions.
Contribute to running our compensation programs that support our wider organisational philosophy while ensuring strong governance.
Develop and implement reward and recognition frameworks for the full organisational structure at DeepMind.
Lead compensation projects from design through execution, including modelling, project planning, communicating, and training in partnership with the rest of the Reward & Recognition team.
Continuously evaluate the efficiency of compensation programs, innovating and recommending changes to improve the effectiveness of our investment in total rewards.
About you
In order to set you up for success as a Reward & Recognition Partner at Google DeepMind, we look for the following skills and experience:
Experience working on compensation in a tech company, preferably with a machine learning focus.
Knowledge of competitive talent environment in California and US regulations.
Experience of working on complex offers and balancing tensions between hiring needs and longer-term compensation implications.
You are comfortable working autonomously and making decisions under pressure.
Ability to assimilate ambiguous information from a wide variety of sources to provide meaningful and timely insights to inform. decisions, and you are comfortable communicating these findings.
You can run with a brief and are comfortable dealing with some ambiguity. When something you are working on changes, you adapt comfortably with a readiness to learn.
You are proficient using Google Sheets, with strong analytical skills.
You are collaborative in your approach to stakeholder management, and have experience of owning relationships with senior stakeholders. You are highly organised with experience of managing your own workload across an array of activity and projects.
You have experience partnering with other teams and have good communication skills, with a natural ability to build relationships across an organisation, instilling trust and creating understanding.
The US base salary range for this full-time position is between $111,000 - $170,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.