AI Safety Expert - Fully Remote | Upto $22/hr

Obsidian; Sydney; Remote; AUD 127,000 - 183,000; Full time

Job summary

Mercor is assembling a remote AI safety red team focused on testing conversational models with adversarial inputs, bias checks, and content probes. The role requires strong judgment of language and content in English and Malayalam, with rigorous attention to detail and a structured, guideline-driven approach.

You will generate reproducible data and attack case reports, contributing to safer AI for customers while collaborating with cross-functional teams in a flexible, remote environment.

Qualifications

• Strong judgment about language and content, able to judge accuracy and appropriateness.
• Rigorous attention to subtle errors, inconsistencies, and gaps.
• Ability to follow guidelines and quality standards consistently.

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

Adversarial ML

Cybersecurity

Risk analysis

Written communication

Structured thinking

Adaptability

English proficiency

Malayalam language

Job description

Location: Remote

Fluent Language Skills Required: English & Malayalam. Native fluency in English and Malayalam 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 strong judgment about language and content: you can tell whether an AI response is accurate, complete, and appropriate, and explain why

• You’re rigorous: you notice subtle errors, inconsistencies, and gaps that others skim past

• You’re structured: you work to guidelines and quality standards consistently, not ad hoc

• You’re communicative: you explain your reasoning clearly to technical and non-technical audiences

• You’re adaptable: you thrive moving across projects, task types, 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