ActiveFence
ActiveFence
ActiveFence onlayn platformalar uchun ishonch va xavfsizlikka ixtisoslashgan kiberxavfsizlik hamda sun’iy intellekt kompaniyasidir. Kompaniyaning to‘liq texnologik yechimi razvedka tadqiqotlari, sun’iy intellekt asosida zararli kontentni aniqlash va kontentni moderatsiya qilish vositalarini birlashtirib, platformalarga bolalarni ekspluatatsiya qilish, dezinformatsiya, nafrat tili, terrorizm, yalang‘ochlik, firibgarlik va onlayn muhitdagi boshqa zararlar kabi xatarlarni bartaraf etishga yordam beradi. ActiveFence turli hajmdagi ishonch va xavfsizlik jamoalarini qo‘llab-quvvatlab, butun dunyo bo‘ylab 100 dan ortiq tilda uch milliarddan ziyod foydalanuvchini himoya qilishga ko‘maklashadi.

AI Red Team – GenAI Adversarial Evaluation at ActiveFence

Develop adversarial attacks, datasets, and benchmarks for ActiveFence’s AI security platform. Test LLM robustness through red teaming and vulnerability research.

Tavsif

  • Design new adversarial attacks.
  • Help build scalable systems for generating and testing attacks at scale.
  • Assess attacks for quality, effectiveness, novelty, and reproducibility.
  • Discover emerging attack patterns and model vulnerabilities.
  • Create adversarial datasets, benchmarks, and regression tests.
  • Share findings, methods, and structured attack data with Data Science, Security, and Engineering teams.
  • Contribute to stronger model robustness and defenses.

Talablar

  • At least three years of professional experience in cybersecurity, security research, red teaming, or a related security field.
  • Bachelor’s degree in Data Science, Computer Engineering, Computer Science, or a closely related technical field.
  • Strong knowledge of large language models, prompt injection, and AI security.
  • Experience in red teaming, security research, or adversarial testing.
  • Strong Python and automation skills.
  • Creative problem-solving skills and the ability to develop new attack techniques.
  • Ability to analyze results and communicate findings clearly.
  • Offensive cybersecurity certifications such as OSWA, OSWE, OSCE3, SEC542, or SEC522 are preferred.

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