# Researcher, Misalignment Research

**Company:** [OpenAI](https://hotfix.jobs/companies/openai)
**Location:** San Francisco, CA
**Role:** AI Research
**Salary:** $295k – $445k/yr
**Experience:** 4+ years
**Skills:** Ai Safety, Red-Teaming, Adversarial Ml, Machine Learning, Evaluation Infrastructure, LLMs, Deceptive Alignment, Scheming Detection, Power-Seeking, Ml Security
**Posted:** 2026-04-28

> Designs worst-case demonstrations and adversarial evaluations to uncover AGI misalignment risks like deception and power-seeking. Builds automated stress-testing infrastructure and researches alignment failure modes to inform OpenAI's safety strategy. Requires 4+ years in AI red-teaming or adversarial ML.

## Job Description

## Responsibilities
- Design and implement worst-case demonstrations that make AGI alignment risks concrete for stakeholders, focused on high stakes use cases.
- Develop adversarial and system-level evaluations grounded in those demonstrations, driving adoption across OpenAI.
- Create automated tools and infrastructure to scale automated red-teaming and stress testing.
- Conduct research on failure modes of alignment techniques and propose improvements.
- Publish influential internal or external papers that shift safety strategy or industry practice.
- Partner with engineering, research, policy, and legal teams to integrate findings into product safeguards and governance processes.
- Mentor engineers and researchers, fostering a culture of rigorous, impact-oriented safety work.

## Requirements
- Passionate about red-teaming and AI safety, thinking about these problems constantly and aligning with OpenAI's mission.
- 4+ years of experience in AI red-teaming, security research, adversarial ML, or related safety fields.
- Strong research track record—publications, open-source projects, or high-impact internal work—demonstrating creativity in uncovering and exploiting system weaknesses.
- Fluent in modern ML / AI techniques and comfortable hacking on large-scale codebases and evaluation infrastructure.
- Communicate clearly with both technical and non-technical audiences, translating complex findings into actionable recommendations.
- Enjoy collaboration and can drive cross-functional projects that span research, engineering, and policy.

## Nice-to-Haves
- Ph.D., master’s degree, or equivalent experience in computer science, machine learning, security, or a related discipline.

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