Applied Safety Research Engineer, Safeguards

Details

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.

Role overview

We are looking for a research-oriented engineer to develop the methods that make our safety evaluations representative, robust, and informative. You'll work on questions like: How do we measure whether a model is safe? How do we create evaluations that reflect real-world usage rather than synthetic benchmarks? How do we know our graders are accurate?

This role sits at the intersection of applied ML research and engineering. You'll design experiments to improve how we evaluate model behavior, then ship those methods into pipelines that inform model training and deployment decisions. Your work will directly shape how Anthropic understands and improves the safety of our models across misuse, prompt injection, and user well-being.

Responsibilities

• Design and run experiments to improve evaluation quality—develop methods to generate representative test data, simulate realistic user behavior, and validate grading accuracy
• Research how different factors (multi-turn conversations, tools, long context, user diversity) impact model safety behavior
• Analyze evaluation coverage to identify gaps and inform where better measurement is needed
• Productionize successful research into evaluation pipelines that run during model training, launch and beyond
• Collaborate with Policy and Enforcement to translate real-world harm patterns into measurable evaluations
• Build tooling that enables policy experts to create and iterate on evaluations
• Surface findings to research and training teams to drive upstream model improvements

Requirements / Qualifications

• 4+ years of software engineering or ML engineering experience
• Proficient in Python and comfortable working across the stack
• Experience building and maintaining data pipelines
• Comfortable with data analysis and able to draw insights from large datasets
• Experience with LLMs and understanding of their capabilities and failure modes
• Ability to move fluidly between prototyping and production-quality code
• Comfortable solving ambiguous problems and translating them into concrete experiments
• Care deeply about AI safety and want your work to have real impact

Education: At least a Bachelor's degree in a related field or equivalent experience.

Strong candidates may also have experience with

• Red teaming, adversarial testing, or jailbreak research on AI systems
• Building or contributing to LLM evaluation frameworks or benchmarks
• Trust and safety, content moderation, or abuse detection systems
• Synthetic data generation or data augmentation
• Distributed systems or large-scale data processing
• Prompt engineering or LLM application development

Compensation

Annual Salary: $320,000 - $405,000 USD

Our total compensation package for full-time employees includes equity and benefits.

Logistics

• Location: San Francisco, CA
• Location-based hybrid policy: currently expect all staff to be in one of our offices at least 25% of the time
• Visa sponsorship: Anthropic sponsors visas and retains an immigration lawyer to assist, though not every role/candidate may be sponsorable

About working at Anthropic / Culture

We work as a single cohesive team on a few large-scale research efforts, value collaboration and communication, and prioritize high-impact work toward steerable, trustworthy AI. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office space in San Francisco.

Apply / Candidate guidance

Anthropic encourages applicants even if they do not meet every qualification. They also provide guidance on using AI in the application process and warn about recruitment scams (official recruiters contact from @anthropic.com).