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AI Safety Expert - Adversarial ML

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: mercor
Full Time position
Listed on 2026-10-12
Job specializations:
  • IT/Tech
    AI Evaluation, Data Annotation/ AI Labeling
Salary/Wage Range or Industry Benchmark: 16 - 22 USD Hourly USD 16.00 22.00 HOUR
Job Description & How to Apply Below
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 & Odia

Type

Contract

Compensation

$16–$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. Follow taxonomies, benchmarks, and playbooks to ensure consistent testing.
  • Document reproducibly. Produce reports, datasets, and attack cases that customers can act on.
  • Work independently and asynchronously . Thrive in flexible hours while improving AI model performance .
Qualifications – Must-Have
  • Native fluency in English and Odia .
  • Strong judgment about language and content.
  • Rigorous attention to detail and consistency.
  • Structured approach to guidelines and quality standards.
  • Clear communication with technical and non-technical audiences.
  • Adaptability across projects, task types, and customers.
Qualifications – Preferred
  • Experience in Adversarial ML : jailbreak datasets, prompt injection, RLHF/DPO attacks, model extraction.
  • Background in Cybersecurity : penetration testing, exploit development, reverse engineering.
  • Knowledge of socio-technical risk: harassment/disinfo probing, abuse analysis, conversational AI testing.
  • Creative probing skills: psychology, acting, writing for unconventional adversarial thinking.
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