Posted:
12/17/2024, 5:05:50 AM
Location(s):
London, England, United Kingdom ⋅ England, United Kingdom
Experience Level(s):
Senior
Field(s):
Legal & Compliance
Workplace Type:
Hybrid
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
We are looking for an experienced UK-based Public Policy expert to advance practical governance of increasingly powerful AI systems by building relationships with external stakeholders, develop substantive policy positions and papers and engage in regular outreach to drive progress in AI policy and AI safety, drawing upon established relationships with key policymakers and their staffs in London. As part of this role you will collaborate with a dynamic, geographically distributed policy team on a variety of other projects, including analyzing policy proposals, drafting submissions for public comment, planning and assisting policy campaigns in the UK and Europe, and also providing policy advice to technical colleagues which you will work alongside in London. This role is crucial to advancing Anthropic's mission in the UK, shaping AI governance to balance safety, innovation, and UK competitiveness.
The expected salary range for this position is:
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Website: https://www.anthropic.com/
Headquarter Location: San Francisco, California, United States
Employee Count: 251-500
Year Founded: 2021
IPO Status: Private
Last Funding Type: Series D
Industries: Artificial Intelligence (AI) ⋅ Generative AI ⋅ Information Technology ⋅ Machine Learning