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ML​/Research Engineer, Safeguards

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: anthropic
Full Time position
Listed on 2026-01-14
Job specializations:
  • Software Development
    Data Scientist, AI Engineer
Salary/Wage Range or Industry Benchmark: 350000 USD Yearly USD 350000.00 YEAR
Job Description & How to Apply Below
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.

About the role

We are looking for ML Engineers and Research Engineers to help detect and mitigate misuse of our AI systems. As a member of the Safeguards ML team, you will build systems that identify harmful use—from individual policy violations to sophisticated, coordinated attacks—and develop defenses that keep our products safe as capabilities advance. You will also work on systems that protect user wellbeing and ensure our models behave appropriately across a wide range of contexts.

This work feeds directly into Anthropic's Responsible Scaling Policy commitments.

Responsibilities

• Develop classifiers to detect misuse and anomalous behavior s includes developing synthetic data pipelines for training classifiers and methods to automatically source representative evaluations to iterate on

• Build systems to monitor for harms that span multiple exchanges, such as coordinated cyber attacks and influence operations, and develop new methods for aggregating and analyzing signals across contexts

• Evaluate and improve the safety of agentic products—developing both threat models and environments to test for agentic risks, and developing and deploying mitigations for prompt injection attacks

• Conduct research on automated red‑teaming, adversarial robustness, and other research that helps test for or find misuse

You may be a good fit if you

• Have 4+ years of experience in ML engineering, research engineering, or applied research, in academia or industry

• Have proficiency in Python and experience building ML systems

• Are comfortable working across the research-to-deployment pipeline, from exploratory experiments to production systems

• Are worried about misuse risks of AI systems, and want to work to mitigate them

• Have strong communication skills and ability to explain complex technical concepts to non‑technical stakeholders

Strong candidates may also have experience with

• Language modeling and transformers

• Building classifiers, anomaly detection systems, or behavioral ML

• Adversarial machine learning or red‑teaming

• Interpretability or probes

The annual compensation range for this role is 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. Our total compensation package for full‑time employees includes equity and benefits.

$350,000 - $500,000 USD

Logistics

Education requirements:

We require at least a Bachelor’s degree in a related field or equivalent experience.

Location-based hybrid policy:
Staff are expected to be in one of our offices at least 25% of the time. Some roles may require more office time.

Visa sponsorship:
We sponsor visas and will make reasonable efforts to secure a visa if an offer is extended.

We encourage you to apply even if you do not meet every single qualification. Representation matters to us, and we value diverse perspectives in our team.

Your safety matters to us. Recruiters will only contact you  email addresses. Beware of scams asking for money or banking information. If unsure, visit  for confirmed positions.

Equal Employment Opportunity

All employment decisions are made without regard to race, color, religion, gender identity and expression, sexual orientation, national origin, genetic information, disability, veteran status, or any protected class. Locations and foreign or future foreign travel requirements are policy only and not disqualifying.

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