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Remote Ai Safety Jobs (NOW HIRING)

Weekday AI

AI Safety & Red Teaming Specialist

Remote We are looking for an experienced AI Safety & Red Teaming Specialist to help evaluate and strengthen the safety, security, and robustness of next-generation AI systems. In this role, you will ...

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How much do remote ai safety jobs pay per hour?

As of Jul 6, 2026, the average hourly pay for remote ai safety in the United States is $32.38, according to ZipRecruiter salary data. Most workers in this role earn between $25.48 and $39.18 per hour, depending on experience, location, and employer.

What is the difference between Remote Ai Safety vs Remote Ai Ethics Specialist?

AspectRemote Ai SafetyRemote Ai Ethics Specialist
Required CredentialsAI safety certifications, technical background in machine learningEthics certifications, background in philosophy or social sciences
Work EnvironmentResearch labs, tech companies, remote teams focused on AI safetyPolicy organizations, tech firms, remote roles emphasizing ethical AI use
Industry UsagePrimarily in AI safety research and developmentIn AI policy, ethics compliance, and responsible AI deployment

Remote Ai Safety focuses on developing and implementing safety measures for AI systems, often requiring technical expertise. Remote Ai Ethics Specialist emphasizes ethical considerations, policies, and societal impacts of AI. Both roles collaborate but differ mainly in their focus—technical safety versus ethical governance.

What are some common challenges faced by professionals working in remote AI Safety roles, and how can they be addressed?

Professionals in remote AI Safety roles often encounter challenges such as collaborating across time zones, staying updated on rapidly evolving AI risks, and communicating complex safety concepts to non-technical stakeholders. To address these issues, it's helpful to establish clear communication protocols, participate in regular virtual meetings, and leverage collaborative tools like shared documentation and chat platforms. Additionally, staying engaged in online AI safety communities and continuous learning are key practices for remaining effective and informed in this dynamic field.

What are the key skills and qualifications needed to thrive as a Remote AI Safety Specialist, and why are they important?

To thrive as a Remote AI Safety Specialist, you need a strong background in machine learning, computer science, and ethics, often supported by an advanced degree in a related field. Familiarity with tools like Python, TensorFlow or PyTorch, and experience with safety analysis frameworks or relevant certifications are highly valued. Excellent problem-solving, critical thinking, and clear written communication skills are crucial for collaborating remotely and addressing complex safety concerns. These abilities ensure the development and deployment of reliable, ethical AI systems that minimize risk and comply with industry standards.

What is a Remote AI Safety job?

A Remote AI Safety job involves working from a location outside of a traditional office to research, develop, and implement strategies that ensure artificial intelligence systems operate safely and ethically. Professionals in this field focus on minimizing risks associated with AI technologies, such as unintended behavior, bias, or misuse. Tasks may include developing safety protocols, conducting risk assessments, and collaborating with multidisciplinary teams to create robust and reliable AI systems. Remote AI Safety roles are found in academia, industry, and non-profit organizations, allowing experts to contribute globally to the safe advancement of AI.
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Remote Ai Safety jobs near you

AI Safety & Red Teaming Specialist

Weekday AI

Remote

Contractor

Posted 4 days ago

Job description

This role is for one of our clients
$50 - $90/hourpay
Role Title: AI Safety & Red Teaming Specialist
Role Type: Contractor
Location: Remote
We are looking for an experienced AI Safety & Red Teaming Specialist to help evaluate and strengthen the safety, security, and robustness of next-generation AI systems. In this role, you will leverage your expertise in adversarial AI, LLM security, and AI safety to identify vulnerabilities, design evaluation methodologies, and improve the resilience of large language models against real-world threats.
This opportunity is ideal for professionals passionate about AI security, ethical hacking, and developing robust evaluation frameworks for advanced AI systems.
Requirements
Key Responsibilities
  • Design and implement advanced evaluation methodologies for AI system safety, including ethical jailbreak testing, prompt injection detection, LLM red teaming, and tool-use abuse scenarios.
  • Develop cross-domain adversarial testing strategies to uncover complex, multi-turn attack patterns and model vulnerabilities.
  • Build, maintain, and enhance regression test suites to continuously assess jailbreak susceptibility and prompt injection risks.
  • Create comprehensive evaluation frameworks that simulate real-world adversarial threats to improve AI robustness and reliability.
  • Collaborate with technical teams to translate security findings into actionable recommendations for AI safety improvements.
  • Document testing methodologies, findings, and best practices through clear technical reports and presentations for both technical and non-technical stakeholders.
Required Qualifications
  • 2+ years of experience in AI Safety, Adversarial Machine Learning, LLM Red Teaming, AI Security, or a related field.
  • Hands-on experience researching, testing, or identifying vulnerabilities involving prompt injection, ethical jailbreaks, adversarial attacks, or tool-use exploitation.
  • Strong understanding of modern LLM architectures, prompt engineering, and AI safety evaluation methodologies.
  • Experience developing structured security assessments, regression testing frameworks, and adversarial evaluation strategies.
  • Excellent analytical, documentation, and communication skills with the ability to explain complex technical findings clearly.
  • Ability to collaborate effectively within cross-functional technical teams.
Preferred Qualifications
  • Master's or PhD in Computer Science, Cybersecurity, Machine Learning, Artificial Intelligence, or a related discipline.
  • Contributions to AI security research, open-source AI safety tools, conference presentations, or published research.
  • Experience with AI model evaluation frameworks, prompt engineering techniques, and AI security assessment tools.
  • Background in multidisciplinary AI safety, cybersecurity, or adversarial machine learning projects.
Must-Have Skills
  • AI Safety
  • LLM Red Teaming
  • Prompt Injection
  • Adversarial Machine Learning
Good-to-Have Skills
  • Ethical Jailbreaking
  • AI Security
  • Prompt Engineering
  • AI Evaluation Frameworks

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