Security Engineer / Research Engineer, RL Security

Details

Anthropic is hiring an engineer to help secure large-scale reinforcement learning systems. Reinforcement learning enables Claude to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is a large distributed system in which training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts.

This is a hands-on engineering role working in the RL codebase and the underlying infrastructure alongside engineers and researchers. Candidates may come from security engineering backgrounds with an interest in large-scale ML systems, or from ML systems and research engineering backgrounds with an interest in security.

Responsibilities

• Design, build, and operate security controls for RL training systems and their infrastructure.
• Work across orchestration, environments, training, and inference as needed.
• Review designs and code across the RL stack, identify security problems, and fix them.
• Build shared libraries and tooling for RL engineers and researchers.
• Build observability systems to understand the behavior of these systems.
• Work with researchers and performance engineers to ensure security changes preserve training correctness and performance.
• Write clear design documents for systems and tools.

Requirements

• Strong software engineering skills in Python and at least one systems language, such as Rust, C++, or Go.
• Experience designing, building, and operating large-scale distributed systems or production security systems.
• Strong understanding of security fundamentals.
• Working knowledge of Linux, containers, and cloud infrastructure.
• Experience debugging complex problems across many hosts and services.
• Ability to reason about tradeoffs among security, performance, and reliability.
• Strong written communication skills, including experience writing design documents.
• Bachelor’s degree or an equivalent combination of education, training, and experience.
• A field of study relevant to the role, as demonstrated through coursework, training, or professional experience.

Preferred qualifications

• Experience running ML training or inference infrastructure at scale.
• Experience with infrastructure security, including isolation, access control, networking, or identity.
• Experience with container orchestration such as Kubernetes and with sandboxed or virtualized code execution at scale.
• Experience building observability for large fleets.
• Experience supporting research teams or other fast-moving internal users.
• Familiarity with reinforcement learning or large language model training workloads.

Compensation

The annual salary range is $320,000–$405,000 USD.

Benefits and Logistics

• Anthropic expects staff to work from one of its offices at least 25% of the time under its location-based hybrid policy; some roles may require more office time.
• Anthropic sponsors visas, although sponsorship may not be available for every role or candidate. The company retains an immigration lawyer to assist with the process.
• Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration spaces.