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AI Safety Specialist - Fully Remote | Upto $45​/hr

Remote / Online - Candidates ideally in
San Jose, Santa Clara County, California, 95199, USA
Listing for: United States Digital Space LLC
Remote/Work from Home position
Listed on 2026-08-16
Job specializations:
  • IT/Tech
    AI Evaluation, Cybersecurity
Salary/Wage Range or Industry Benchmark: 45 USD Hourly USD 45.00 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 & Portuguese (global)
Type:

Contract Compensation:$29–$45/hour

Location:

Remote

Role Responsibilities
  • Red team conversational AI models and agents by performing jailbreaks, prompt injections, misuse cases, and bias exploitation.
  • Generate high-quality human data by annotating failures, classifying vulnerabilities, and flagging systemic risks.
  • Apply structure by following taxonomies, benchmarks, and playbooks to maintain consistent testing.
  • Document reproducibly by producing reports, datasets, and attack cases that customers can act on.
  • Work independently and asynchronously to improve AI model performance and ensure safety.
Qualifications Must-Have
  • Native fluency in English and Portuguese (global, excluding Brazilian Portuguese).
  • Prior red teaming experience in AI adversarial work, cybersecurity, or socio-technical probing.
  • Strong communication skills to explain risks clearly to technical and non-technical stakeholders.
Preferred
  • Experience in Adversarial ML: jailbreak datasets, prompt injection, RLHF/DPO attacks, model extraction.
  • Cybersecurity skills: penetration testing, exploit development, reverse engineering.
  • Socio-technical risk expertise: harassment/disinfo probing, abuse analysis, conversational AI testing.
  • Creative probing skills: psychology, acting, writing for unconventional adversarial thinking.

Originally posted on Himalayas

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