ML/Research Engineer, Safeguards
Anthropic · San Francisco, CA | New York City, NY · AI Research & Engineering · listed October 9, 2025
The shape of it
Seniority
Mid level
Experience asked
4+ years
Where
Hybrid
Stated pay
$350,000 – $500,000 USD
Requirements listed
5
Length
931 words
In the posting’s own words
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.
What it asks for · 5
- 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
Also a plus
- Language modeling and transformers
- Building classifiers, anomaly detection systems, or behavioral ML
- Adversarial machine learning or red-teaming
- Interpretability or probes
- Reinforcement learning
- High-performance, large-scale ML systems
What the job covers
- 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
Tools and skills named
Models & research
- Machine learning7×
- Evaluations
- Reinforcement learning
Data
- Data pipelines
Languages
- Python
Words the posting leans on
- systems9×
- research5×
- misuse4×
- attacks3×
- classifiers3×
- develop3×
- developing3×
- experience3×
- adversarial2×
- agentic2×
- build systems2×
- building2×
- contexts2×
- coordinated2×
- detect2×
- engineering2×
Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.
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