- 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
- Develop classifiers to detect misuse and anomalous behavior at scale. This 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
Benefits
- Comprehensive health, dental, and vision insurance for you and your dependents
- Inclusive fertility benefits via Carrot Fertility
- 22 weeks of paid parental leave
- Flexible paid time off and absence policies
- Mental health support for you and your dependents
- Competitive salary and equity packages
- Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant
- Retirement plans with competitive matching
- Life and income protection plans
- $500/month flexible wellness and time saver stipend
- Commuter benefits
- Annual education stipend
- Home office stipends
- Relocation support for those moving for Anthropic
- Daily meals and snacks in the office
Have strong communication skills and ability to explain complex technical concepts to non-technical stakeholdersHave proficiency in Python and experience building ML systemsHave 4+ years of experience in ML engineering, research engineering, or applied research, in academia or industryAre worried about misuse risks of AI systems, and want to work to mitigate themAre comfortable working across the research-to-deployment pipeline, from exploratory experiments to production systemsInterpretability or probesBuilding classifiers, anomaly detection systems, or behavioral MLLanguage modeling and transformersAdversarial machine learning or red-teamingWe require at least a Bachelor’s degree in a related field or equivalent experienceReinforcement learningHigh-performance, large-scale ML systems
#J-18808-Ljbffr…