AI Safety Expert - Adversarial ML

Mercor; Toronto; Remote; CAD 80,000 - 120,000; Full time

Job summary

Mercor is building a remote red-team for adversarial testing of conversational AI systems. You will assess how models can be misused and identify vulnerabilities in safe, reproducible ways.

You’ll produce high-quality labeled data and reports to help customers strengthen AI safety across diverse topics, with clear guidelines and wellness support as needed.

Qualifications

• Native-level fluency in English and Telugu required.
• Strong judgment on language safety and content.
• Ability to follow structured testing guidelines.

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

English

Telugu

Job description

Location: Remote

Fluent Language Skills Required: English & Telugu. Native fluency in English and Telugu 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