# ML/Research Engineer, Safeguards

**Company**: Anthropic
**Location**: San Francisco, CA
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $350,000-$500,000 USD
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q116758847

**Apply**: https://job-boards.greenhouse.io/anthropic/jobs/4949336008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_a37329b0-8ec

## Description

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society.

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.

Responsibilities:

- Develop classifiers to detect misuse and anomalous behavior at scale.

- Build systems to monitor for harms that span multiple exchanges, such as coordinated cyber attacks and influence operations.

- Evaluate and improve the safety of agentic products,developing both threat models and environments to test for agentic risks.

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

Requirements:

- 4+ years of experience in ML engineering, research engineering, or applied research.

- Proficiency in Python and experience building ML systems.

- Comfortable working across the research-to-deployment pipeline.

- 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.

- Reinforcement learning.

- High-performance, large-scale ML systems.

The annual compensation range for this role is $350,000-$500,000 USD.

Logistics:

- Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience.

- Required field of study: A field relevant to the role.

- Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time.

- Visa sponsorship: We do sponsor visas.

## Skills

### Required
- Python
- ML systems
- communication skills

### Nice to have
- Language modeling
- transformers
- adversarial machine learning
- red-teaming
- interpretability
- probes
- reinforcement learning
- high-performance ML systems

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/anthropic/jobs/4949336008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)