⚡ Self-Built Using AI

NIPUN
AGGARWAL

Trust & Safety / LLM Training / Content Moderation / Community Management

6+ years keeping platforms and AI systems safe - from content moderation at scale to LLM training across Trust & Safety, Community Management, and AI Governance. Based in New Delhi, open to relocation globally.

6+
Years Exp
04
Domains
10k+
Cases Reviewed
Trust & Safety AI Red Teaming Content Moderation VLA Data Annotation AI Output Evaluation Community Management Adversarial Prompting LLM Safety AI Governance Policy Enforcement Trust & Safety AI Red Teaming Content Moderation VLA Data Annotation AI Output Evaluation Community Management Adversarial Prompting LLM Safety AI Governance Policy Enforcement

FOUR DOMAINS

Real work across real platforms. Click any domain to explore case studies, methodology, and examples.

01 - FEATURED
🧠
LLM TRAINING

End-to-end contribution to large language model development - from building high-quality training datasets through video annotation, to evaluating model outputs, to adversarially stress-testing safety guardrails.

RLHF Safety Evaluation Data Annotation Red Teaming Alignment Adversarial Testing
⚔️
Red Teaming
Adversarial prompting, jailbreak detection, policy gap identification on production LLMs
🎬
Data Annotation (VLA)
Video annotation for robotic, gameplay, and sports action datasets
🤖
AI Output Evaluation
Structured LLM response review for safety, accuracy, and policy compliance
02
🛡️
TRUST & SAFETY

Policy enforcement, escalation management, and platform integrity across Meta, Twitter, and gaming ecosystems.

Policy EnforcementRisk AssessmentEscalationAbuse Prevention
03
🚫
CONTENT MODERATION

High-volume, high-stakes content review across hate speech, violence, CSAM, and policy violations at scale.

Hate SpeechNSFW ReviewSpam DetectionCultural Context
04
🤝
COMMUNITY MANAGEMENT

Sentiment analysis, crisis detection, and abuse pattern reporting for brand communities and platform health.

Sentiment AnalysisCrisis ManagementTrend Reporting
+
New Skill
Coming Soon
Nipun Aggarwal
Available
NIPUN AGGARWAL
Trust & Safety · LLM Training · Content Moderation · Community Management

Started reviewing content at scale in 2019. Six years later, I adversarially test large language models - finding the gaps before bad actors do. I bring a rare combination: the instincts of someone who has reviewed thousands of real harmful cases, and the technical curiosity to understand how AI systems fail.

My background in psychology and history gives me an unusual lens - I think about why systems fail, not just how. I'm building toward AI Governance and Responsible AI.

6+
Yrs Experience
5
Companies
4
Domains
Strengths
Critical Thinking
Assessing intent, context, and severity - not just surface content - before making a call.
Lateral Thinking
Finding edge cases others miss - whether probing model guardrails, evaluating output quality, or spotting patterns in annotation data.
Adaptability
From human content review to LLM training - the same core instincts applied across entirely new domains.
Team Player
Safety work is collaborative - escalations, policy decisions, and reporting all depend on clear cross-functional communication.
Intellectual Curiosity
Two degrees, three certifications, and a career that's deliberately evolved - always looking for the next layer of understanding.
Learn more about me →

GET IN TOUCH

Open to remote roles in Trust & Safety, LLM Training, and AI Governance. If you're building safer AI, I'd like to help.