AI Safety Experts – English, Telugu

Posted 6hrs ago

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Job Description

AI red-teaming contractor probing Mercor’s frontier models with adversarial inputs. Generating human-labeled safety data, vulnerability reports, datasets, and attack cases.

Responsibilities:

  • Red-team conversational AI models and agents using jailbreaks, prompt injections, misuse cases, bias exploitation, and multi-turn manipulation
  • Generate human data by annotating failures, classifying vulnerabilities, and flagging systemic risks
  • Apply taxonomies, benchmarks, and playbooks to keep testing consistent
  • Produce reproducible reports, datasets, and attack cases for customers
  • Review AI outputs involving sensitive topics such as bias, misinformation, or harmful behaviors
  • Uncover vulnerabilities that automated tests miss
  • Expand evaluation coverage and reduce production surprises
  • Help strengthen the safety, robustness, and trustworthiness of frontier AI systems

Requirements:

  • Native fluency in English and Telugu is required
  • Strong judgment about language and content; ability to assess whether AI responses are accurate, complete, and appropriate and explain why
  • Rigorous attention to subtle errors, inconsistencies, and gaps
  • Ability to follow guidelines and quality standards consistently
  • Ability to explain reasoning clearly to technical and non-technical audiences
  • Adaptability across projects, task types, and customers
  • Independent contractor status
  • Must not be an H1-B or STEM OPT candidate
  • Nice-to-have specialties: adversarial ML, cybersecurity, socio-technical risk, or creative probing

Benefits:

  • Fully remote work
  • Flexible schedule / work on your own schedule
  • Weekly payments via Stripe or Wise
  • Projects may be extended, shortened, or concluded early depending on needs and performance
  • Wellness resources and clear guidelines for higher-sensitivity projects
  • Competitive pay
  • Reasonable accommodations upon request
  • Referral bonus of up to $90 for each successful referral, subject to limits