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Freelancer - GenAI Analyst (Remote) at ACTIVEFENCE INC
Ramat Gan, Tel-Aviv District, Israel -
Full Time

Start Date

Immediate

Expiry Date

15 Feb, 26

Salary

0.0

Posted On

17 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Generative AI, Adversarial Prompts, Data Annotation, Quality Control, Model Evaluation, Prompt Engineering, Safety Analysis, Cultural Fluency

Industry

Software Development

Description
Your tasks will involve writing adversarial prompts to identify weaknesses in various cutting-edge AI models, including Large Language Models (LLMs), Text-to-Image, Text-to-Video, Multi-Modal models, AI Agents and beyond. You’ll also manage and analyze datasets to ensure the generation of high-quality outputs and actionable insights that contribute to AI safety research. Key Responsibilities Design adversarial prompts to test AI systems across multiple modalities. Identify, categorize, and document model weaknesses or unsafe outputs. Support data annotation, curation, and quality control processes. Summarize findings into structured reports or data templates. Requirements Proven experience with Generative AI models is essential, though direct technical experience is not a prerequisite. Understanding of risk taxonomies (e.g., harm categories, policy tiers). Command of English at a near-native level. Attention to detail, organizational capabilities Ability to manage multiple tasks simultaneously and meet deadlines. Additional Wants: Familiarity with various model types (Text-to-Text, Text-to-Image) is desirable. Experience with prompt injection techniques, jailbreaks and red-teaming techniques. Prior work in model evaluation,prompt engineering, or safety analysis. Regional expertise or cultural fluency in specific geopolitical areas. About ActiveFence null

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Responsibilities
The role involves designing adversarial prompts to test AI systems and identifying weaknesses in various AI models. Additionally, the analyst will manage datasets to ensure high-quality outputs and actionable insights for AI safety research.