Remote | Kannada-English AI Safety Red Team Evaluator — $20–$30/hour

About the Role

What You Will Do

• Test AI systems using structured adversarial scenarios to identify safety weaknesses and classify risks
• Review English and Kannada AI outputs for safety, reliability, bias, misinformation, and harmful-behavior risks
• Stress-test conversational AI models and agents using structured adversarial scenarios
• Evaluate model behavior across multi-turn conversations, sensitive topics, and edge-case prompts
• Identify vulnerabilities that require stronger safety controls, clearer refusals, or improved response quality
• Annotate failures, classify vulnerabilities, and flag recurring safety patterns
• Apply taxonomies, benchmarks, and project-specific playbooks to keep testing consistent
• Assess misuse cases, bias exploitation, prompt-injection scenarios, and socio-technical risk patterns at a high level
• Generate high-quality human evaluation data through careful review and structured judgment
• Produce clear reports, datasets, test cases, and written summaries that support model improvement
• Document findings reproducibly so results can be reviewed, compared, and acted upon
• Explain risks clearly for both technical and non-technical audiences

What We Are Looking For

• Native-level fluency in both English and Kannada
• Prior experience in AI red teaming, adversarial testing, cybersecurity, trust and safety, socio-technical risk review, or conversational AI evaluation
• Ability to think adversarially while staying structured, careful, and methodical
• Experience using frameworks, benchmarks, or rubrics rather than unstructured testing alone
• Strong written communication skills and ability to explain safety findings clearly
• Comfort reviewing text-based content involving sensitive topics under clear guidelines
• Adaptability across project types, safety categories, and evaluation workflows
• Formal degree requirements may vary based on project needs
• Backgrounds in AI safety, cybersecurity, linguistics, policy, trust and safety, social science, psychology, writing, data evaluation, or technical analysis may be highly relevant
• Practical experience in red team testing, model evaluation, content risk analysis, or structured review work may also be valuable

Nice to Have

• Experience with adversarial ML concepts, jailbreak datasets, prompt injection, RLHF/DPO attack patterns, or model behavior testing
• Cybersecurity experience such as penetration testing, exploit analysis, reverse engineering, or security assessment
• Socio-technical risk experience involving harassment, misinformation, abuse analysis, bias testing, or conversational AI safety
• Creative probing background, including psychology, acting, writing, role-play design, or unconventional adversarial thinking
• Experience producing reproducible reports, labeled datasets, structured risk notes, or benchmark-style evaluation artifacts

Benefits and Perks

• Competitive hourly rate of $20-$30 per hour
• Opportunity to work on flexible assignments and contribute to stronger, safer AI systems
• Collaborative and dynamic work environment with a team of experienced professionals
• Professional development opportunities in AI safety, red team testing, and related fields
• Flexible work arrangements and remote work options
• Access to cutting-edge tools and technologies in AI safety and evaluation
• Recognition and rewards for outstanding performance and contributions to the team
• Comprehensive support for ongoing education and training in AI safety and related fields

• Develop a strong portfolio showcasing your experience in AI safety evaluation, red team testing, and adversarial review to stand out as a candidate.
• Highlight your ability to communicate complex safety findings clearly and effectively, both in writing and verbally.
• Be prepared to provide specific examples of your experience with structured adversarial scenarios, risk classification, and vulnerability annotation.
• Familiarize yourself with the latest developments in AI safety, red team testing, and adversarial ML concepts to demonstrate your expertise.
• Emphasize your ability to work with sensitive topics and adapt to different project types, safety categories, and evaluation workflows.
• Consider obtaining certifications in AI safety, cybersecurity, or related fields to enhance your qualifications and demonstrate your commitment to the field.
• Practice explaining technical concepts to non-technical audiences to improve your communication skills and increase your chances of success in the role.