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Adversarial AI Specialist - Fully Remote

Remote / Online - Candidates ideally in
San Francisco, San Francisco County, California, 94199, USA
Listing for: mercor
Remote/Work from Home position
Listed on 2026-10-12
Job specializations:
  • IT/Tech
    AI Evaluation, Cybersecurity, Data Annotation/ AI Labeling
Salary/Wage Range or Industry Benchmark: 22 USD Hourly USD 22.00 HOUR
Job Description & How to Apply Below
Position: Adversarial AI Specialist - Fully Remote | Upto $22/hr
About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey . Position: AI Safety Experts — English & Urdu Type:
Contract Compensation: $20–$22/hour

Location:

Remote

Role Responsibilities
  • Red team conversational AI models and agents. Conduct jailbreaks, prompt injections, misuse cases, and bias exploitation.
  • Generate high-quality human data. Annotate failures, classify vulnerabilities, and flag systemic risks.
  • Apply structure using taxonomies, benchmarks, and playbooks to maintain testing consistency.
  • Document reproducibly. Produce reports, datasets, and attack cases that customers can act on.
  • Work independently and asynchronously to meet deadlines while improving AI model performance.
Qualifications Must-Have
  • Native fluency in English and Urdu.
  • Prior red teaming experience in AI adversarial work , cybersecurity , or socio-technical probing.
  • Strong communication skills to explain risks to technical and non-technical stakeholders.
Preferred
  • Experience in Adversarial ML : jailbreak datasets, prompt injection, RLHF/DPO attacks, model extraction.
  • Background in Cybersecurity : penetration testing, exploit development, reverse engineering.
  • Expertise in socio-technical risk: harassment/disinfo probing, abuse analysis, conversational AI testing.
  • Creative probing skills in psychology, acting, or writing for unconventional adversarial thinking.
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