AI Safety Specialist - Fully Remote | Upto $35/hr

Obsidian; San Francisco (CA); Remote; USD 90,000 - 130,000; Full time

Job summary

Mercor is seeking a remote red-team data expert to probe AI models with adversarial inputs, surface vulnerabilities, and generate high-quality data for safer AI systems. English and Thai fluency are required, with topics ranging from bias to harmful content handled under clear guidelines.

You’ll document results and collaborate across projects for robust safety testing. This role focuses on reproducible artifacts, standardized taxonomies, and cross-functional communication to stakeholders,

Qualifications

• Prior red teaming experience (AI adversarial work, cybersecurity, socio-technical probing).
• Curious and adversarial: you instinctively push systems to breaking points.
• Structured: you use frameworks or benchmarks, not just random hacks.
• Communicative: you explain risks clearly to technical and non-technical stakeholders.
• Adaptable: thrive on moving across projects and customers.

Responsibilities

• Red team conversational AI models and agents: jailbreaks, prompt injections, misuse cases, bias exploitation, multi-turn manipulation
• Generate high-quality human data: annotate failures, classify vulnerabilities, and flag systemic risks
• Apply structure: follow taxonomies, benchmarks, and playbooks to keep testing consistent
• Document reproducibly: produce reports, datasets, and attack cases customers can act on

Skills

Red team

Adversarial AI

Cybersecurity

Socio-technical risk

Structured testing

Clear communication

Adaptable

Job description

Location: Remote

Fluent Language Skills Required: English & Thai. Native fluency in English and Thai is required for this position.

Why This Role Exists

At Mercor, we believe the safest AI is the one that’s already been attacked — by us. We are assembling a red team for this project - human data experts who probe AI models with adversarial inputs, surface vulnerabilities, and generate the red team data that makes AI safer for our customers.

This project involves reviewing AI outputs that touch on sensitive topics such as bias, misinformation, or harmful behaviors. All work is text-based, and participation in higher-sensitivity projects is optional and supported by clear guidelines and wellness resources. Before being exposed to any content, the topics will be clearly communicated.

What You’ll Do

• Red team conversational AI models and agents: jailbreaks, prompt injections, misuse cases, bias exploitation, multi-turn manipulation

• Generate high-quality human data: annotate failures, classify vulnerabilities, and flag systemic risks

• Apply structure: follow taxonomies, benchmarks, and playbooks to keep testing consistent

• Document reproducibly: produce reports, datasets, and attack cases customers can act on

Who You Are

• You bring prior red teaming experience (AI adversarial work, cybersecurity, socio-technical probing)

• You’re curious and adversarial: you instinctively push systems to breaking points

• You’re structured: you use frameworks or benchmarks, not just random hacks

• You’re communicative: you explain risks clearly to technical and non-technical stakeholders

• You’re adaptable: thrive on moving across projects and customers

Nice-to-Have Specialties

• Adversarial ML: jailbreak datasets, prompt injection, RLHF/DPO attacks, model extraction

• Cybersecurity: penetration testing, exploit development, reverse engineering

• Socio-technical risk: harassment/disinfo probing, abuse analysis, conversational AI testing

• Creative probing: psychology, acting, writing for unconventional adversarial thinking

What Success Looks Like

• You uncover vulnerabilities automated tests miss

• You deliver reproducible artifacts that strengthen customer AI systems

• Evaluation coverage expands: more scenarios tested, fewer surprises in production

• Mercor customers trust the safety of their AI because you’ve already probed it like an adversary

Why Join Mercor

• Build experience in human data-driven AI red teaming at the frontier of safety

• Play a direct role in making AI systems more robust, safe, and trustworthy