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.
About the role
We’re hiring an experienced writer and editor for our Communications team. In this role, you’ll help bring complex ideas about AI research, AI safety, and the economic and social impacts of AI to broader audiences in accessible, compelling ways. In this role, you'll work at the intersection of technical research and public understanding, crafting narratives that illuminate Anthropic’s research. You'll collaborate with researchers, policy experts, and product designers to level up our owned editorial and develop content that engages diverse audiences—from policymakers to educators to the general public.
You'll help shape how Anthropic communicates our research and advances the public discourse around the economic and societal impacts of AI. This role will combine deep technical understanding with creativity, excellent writing and communication skills, and knowledge of the media landscape to make a major impact on how our ideas get out into the world.
Responsibilities:
- Create engaging written (and other) content about Anthropic's research and broader AI-related questions for our website and other platforms
- Collaborate with researchers across the org to identify compelling angles and stories from their technical work
- Develop editorial strategies that advance understanding of AI safety and development and build new, larger audiences for our work
- Write and edit content ranging from blog posts and articles to research summaries and educational materials
- Work with our communications and brand/creative teams to develop multimedia content strategies
- Contribute to Anthropic's thought leadership in AI research, safety, and ethical discussions, and in particular advance the discussions on the economic and societal impacts of AI
You may be a good fit if you:
- Have a proven track record of writing about complex technical or scientific topics for broad audiences
- Apply critical thinking and analysis to all aspects of communications
- Possess strong knowledge of machine learning and/or economic concepts, or demonstrate exceptional ability to quickly master technical subjects
- Have experience working directly with researchers or technical experts to develop content, and excel at finding compelling narratives within technical work
- Are passionate about making complex ideas accessible without sacrificing accuracy
- Care deeply about AI safety and responsible technology development
- Enjoy collaborating with multiple teams and managing multiple projects
- Are comfortable adapting your writing/communications style for different audiences and formats
Strong candidates may also have:
- An advanced degree in computer science/machine learning, economics, or a related field
- Experience writing publicly about AI, economics, or related technical fields
- A background in academic research or technical communications
- A portfolio demonstrating creative approaches to technical communication
- Experience with multimedia content development
- A deep understanding of the AI policy landscape
- A track record of building engaged audiences around technical content
The expected salary range for this position is:
Annual Salary:
$240,000—$300,000 USD
Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
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.
How we're different
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.
Come work with us!
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.
Top Skills
What We Do
Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.
