Security Engineer / Research Engineer, RL Security

VulnU; New York (NY); Hybrid; USD 320,000 - 405,000; Full time

Benefits offered by this job

Equity

Visa sponsorship

22 weeks parental leave

Flexible PTO

Retirement match

Learning budget

Home-office stipend

Job summary

Anthropic is hiring a Security Engineer / Research Engineer to design and operate security controls across large-scale RL training systems and infrastructure. You will work on the RL codebase and its environment, balancing security with performance in a fast-moving ML platform.

The role requires strong Python and a systems language (Rust/Go/C++), plus experience with Linux, containers, and cloud infrastructure. Collaboration with researchers and performance engineers is essential.

Qualifications

• Strong software engineering in Python and at least one systems language (Rust/C++/Go).
• Experience designing, building, and operating large-scale distributed or security systems in production.
• Solid understanding of security fundamentals.

Responsibilities

• Design, build, and operate security controls for RL training systems and the infrastructure they run on.
• Review designs and code to find security problems and fix them across the stack.
• Build observability and tooling for RL infrastructure security.

Skills

Python

Rust

Go

Distributed systems

Security fundamentals

Education

Bachelor's degree

Tools

Kubernetes

Docker

Linux

Job description

# Security Engineer / Research Engineer, RL SecurityAnthropic · anthropic.comCategory: Security EngineeringLocation: San Francisco, CA | New York City, NY | Seattle, WA## Quality of lifeWhat the posting states. Hover or tap a perk to see the line it came from.* Equity* Sponsors visas* 22 weeks parental leave* Flexible PTO* Retirement match* Learning budget* Home-office stipendAbout AnthropicAnthropic’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 roleReinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is a large distributed system: training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts. As an engineer in RL Engineering, you'll work on keeping that system secure as it scales.This is a hands-on engineering role. You'll work in the RL codebase and the infrastructure underneath it, alongside the engineers and researchers who build and use it. The system is large and changes as fast as the research does, so security work here has to keep up with that pace without costing performance or velocity.We're hiring from two backgrounds: security engineers who want to work on large-scale ML systems, and ML systems or research engineers who want to work on security. Strong candidates have depth in one and real interest in the other.Key responsibilitiesDesign, build, and operate security controls for RL training systems and the infrastructure they run onWork across the stack (orchestration, environments, training, inference) wherever the work is neededReview designs and code across the RL stack, find security problems, and fix themBuild shared libraries and tooling that other RL engineers and researchers build onBuild the observability needed to understand what these systems are doingWork with researchers and performance engineers to make sure security changes preserve training correctness and performanceWrite clear design documents for what you buildMinimum qualificationsStrong software engineering skills in Python and at least one systems language such as Rust, C++, or GoExperience designing, building, and operating large-scale distributed systems or security systems in productionStrong understanding of security fundamentalsWorking knowledge of Linux, containers, and cloud infrastructureExperience debugging complex problems across many hosts and servicesAbility to reason about tradeoffs between security, performance, and reliabilityStrong written communication, including design documentsPreferred qualificationsExperience running ML training or inference infrastructure at scaleExperience with infrastructure security, such as isolation, access control, networking, or identityExperience with container orchestration such as Kubernetes, and with sandboxed or virtualized code execution at scaleExperience building observability for large fleetsExperience supporting research teams or other fast-moving internal usersFamiliarity with reinforcement learning or large language model training workloadsThe annual compensation range for this role is listed below.For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.Annual Salary:$320,000 $405,000 USDLogisticsMinimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experienceRequired field of study: A field relevant to the role as demonstrated through coursework, training, or professional experienceMinimum years of experience: Years of experience required will correlate with the internal job level requirements for the positionLocation-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.Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.How we're differentWe 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.