AI Safety Expert - Red Team

Mercor

Lisboa

Teletrabalho

EUR 78 000 - 130 000

Tempo integral

14 dias+
Gerador de candidaturas

Uma candidatura completa num minuto — currículo personalizado e carta de apresentação, prontos a enviar.

Ultrapassa os filtros ATS

Resumo da oferta

Mercor is building a dedicated red team to test AI safety by probing conversational models through jailbreaks, prompt injections, and bias scenarios. This role centers on generating high-quality human data, classifying vulnerabilities, and documenting findings with structured reports that help customers strengthen AI systems.

The work spans multiple projects and clients, with a strong emphasis on clear communication and reproducibility.

Qualificações

  • Red team experience with AI adversarial work or cybersecurity.
  • Clear, structured thinking and the ability to follow frameworks or playbooks.

Responsabilidades

  • 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

Conhecimentos

Red team experience
Adversarial mindset
Structured approach
Communication
Adaptability

Descrição da oferta de emprego

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’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
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