Applied Safety Research Engineer, Safeguards

About Anthropic

Anthropics 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 are looking for a research-oriented engineer to develop the methods that make our safety evaluations representative robust and informative. Youll 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. Youll 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 qualitydeveloping 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 we need better measurement

• 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

You may be a good fit if you:

• Have 4 years of software engineering or ML engineering experience

• Are proficient in Python and comfortable working across the stack

• Have experience building and maintaining data pipelines

• Are comfortable with data analysis and can draw insights from large datasets

• Have experience with LLMs and understand their capabilities and failure modes

• Can move fluidly between prototyping and production-quality code

• Are excited by ambiguous problems and can translate them into concrete experiments

• Care deeply about AI safety and want your work to have real impact

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

Logistics

Education requirements: We require at least a Bachelors 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 arent 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 youre interested in this work. We think AI systems like the ones were 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 addresses. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money fees or banking information before your first day. If youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

How were 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. Were 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 aboutour policyfor using AI in our application process