AI Safety Expert - Red Team - AI Trainer

Mercor

Lisboa

À distance

EUR 70 000 - 90 000

Plein temps

14 jours+

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Résumé du poste

Mercor is seeking a passionate AI red team specialist to stress-test conversational agents. You will simulate jailbreaks, prompt injections, and bias exploitation to surface vulnerabilities and improve safety across integrations.

You will produce reproducible artifacts, annotate failures, and follow taxonomies and playbooks to keep testing consistent. Remote across markets, you’ll collaborate with diverse teams and customers to strengthen AI systems.

Qualifications

  • Red teaming experience in AI adversarial work or cybersecurity
  • Curious and adversarial mindset that pushes systems to breaking points
  • Structured approach using frameworks or benchmarks
  • Strong communication to explain risks to diverse stakeholders
  • Adaptable to moving across projects and customers

Responsabilités

  • Red team conversational AI models: jailbreaks, prompt injections, misuse cases, bias exploitation
  • Generate high-quality human data: annotate failures, classify vulnerabilities, flag risks
  • Apply structure: follow taxonomies, benchmarks, playbooks for consistent testing
  • Document reproducibly: produce reports, datasets, attack cases for customers

Connaissances

Red team experience
Adversarial thinking
Structured approach
Communication skills
Adaptability
Curiosity

Description du poste

Location: Remote

Fluent Language Skills Required: English & Portuguese (global, excluding Brazilian Portuguese). Native fluency in English and Portuguese (global, excluding Brazilian Portuguese) is required for this position.

Why This Role Exists

At Mercor, we believe the safest AI is the one that is 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

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