Mid-Level, Senior, Expert
About Anthropic
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.
Anthropic's Safeguards organization builds the policies, evaluations, and enforcement systems that define and hold the limits on how Claude can be used. In this role, you'll own our conventional weapons work.
Defining a crisp boundary between acceptable and harmful requests in this domain is difficult, because the underlying components are dual-use: the same capabilities that serve civilian engineering and research can also contribute to a weapons system. Building the threat models, evaluations, and detection systems that hold that boundary is the core of this role.
Conventional weapons are increasingly defined by software, and the risks reach well beyond firearms: from a model operating a weapons system or writing guidance code, to the weaponization of dual-use platforms. The role spans every weapon class, up to autonomous systems that select and engage targets without human authorization.
You will help define the line between prohibited weapons development and legitimate research and engineering work, and how to operationalize the distinction. This will include translating technical judgment into principles that engineers can implement and enforcement teams can act on.
Own and maintain Anthropic's conventional weapons policy, defining the boundary between the activities our models should and should not support
Build the threat models and evaluations that measure how our models could contribute to weapons development, including the software and autonomy components that define modern weapons systems, and keep them current as the technology and its misuse evolve
Partner with engineering to turn the policy into model guardrails, detection systems, and enforcement tooling
Serve as the subject-matter expert for escalations involving conventional weapons content, including rapid response to emerging risks
Build shared understanding of the policy across product, engineering, legal, and leadership, communicating its reasoning to technical and non-technical audiences
Engage external experts as well as government and industry partners, and translate that engagement into stronger policy and enforcement
Have deep, applied expertise in weapons systems and can translate complex technical evidence into sound policy judgments
Experience in a relevant setting, such as a service research laboratory, a defense research or innovation agency, or a company that designs or builds weapons systems
Can write clear, operationally precise policy and explain complex technical topics to non-specialist audiences
Understand the legal frameworks governing weapons and their transfer, and can craft policy that holds up across jurisdictions
Can do rigorous technical analysis of weapons systems using only open sources
Are comfortable with ambiguity and drawn to problems that have no established playbook
Are motivated by preventing misuse without obstructing the legitimate work in the field
A working understanding of machine learning and large language model fundamentals
Hands-on engineering experience in a weapons-relevant technical domain, such as systems engineering, robotics and autonomy, guidance/navigation/control, sensors and signal processing, aerospace or mechanical engineering, materials and energetics, or embedded software
Hands-on experience applying arms export controls (ITAR/EAR) or international arms-control regimes
Experience building or evaluating classifiers, including LLM-based ones, and reasoning about precision and recall for rare, high-consequence categories
Trust & safety or product policy experience at a technology platform
Annual Salary: $245,000 - $285,000 USD
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
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.
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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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
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