Data Security Council of India
Website:
dsci.in
Job details:
Role Summary
The AI Safety Research & Policy Professional will contribute to research, analysis, and knowledge development across emerging AI safety and security issues. The role will involve tracking global AI safety research, evaluation methodologies, standards, policy developments, and emerging risks, and translating these developments into clear, evidence-based insights and practical guidance.
The Professional will work closely with the technical AI safety research and testing function to analyse evaluation findings, identify emerging risk patterns, and connect empirical results with broader AI safety research and frameworks. The role will contribute to research publications, landscape assessments, readiness frameworks, briefings, and other outputs for industry and research partners.
This is a research-focused role requiring strong analytical, writing, and communication skills, along with a good understanding of AI/ML systems and emerging AI safety and security risks. The role is focused on applied AI safety research and knowledge development.
Key Responsibilities
AI Safety Research & Landscape Analysis
- Conduct structured research on emerging AI safety and security risks and developments.
- Track research papers, technical reports, evaluation studies, standards, frameworks, and publications from AI Safety Institutes, research organisations, evaluation labs, standards bodies, and other relevant institutions.
- Monitor developments in AI safety evaluation, assurance, testing, governance, and risk-management approaches.
- Track major developments in frontier and open-weight AI models and assess their potential AI safety and security implications.
- Maintain an organised knowledge base covering relevant AI safety research, frameworks, standards, methodologies, and developments.
- Identify emerging areas of AI safety research that may require further investigation, evaluation, or testing.
- Conduct comparative analysis of international approaches to AI safety and security, with particular attention to developments relevant to India.
Research & Publications
- Prepare research briefs, landscape reports, background papers, technical summaries, and other analytical outputs on AI safety and security topics.
- Review and synthesise technical research papers, evaluation reports, standards, frameworks, and other credible sources.
- Translate complex technical research into clear and accessible analysis for industry, research, and other non-specialist audiences.
- Contribute to periodic AI safety and security landscape assessments.
- Develop evidence-based insights and recommendations based on research findings and available evidence.
- Support the preparation of presentations, briefing materials, articles, reports, and other knowledge products.
- Identify gaps, limitations, and areas of uncertainty within existing AI safety research and evaluation approaches.
AI Safety Frameworks, Standards & Readiness
- Research and analyse AI safety frameworks, standards, evaluation methodologies, and assurance approaches developed by relevant international and national organisations.
- Assess the applicability of existing frameworks and approaches to organisations developing, deploying, or adopting AI systems.
- Contribute to the development of practical AI safety readiness frameworks, assessment approaches, checklists, and guidance.
- Support AI safety and security gap assessments based on established frameworks, standards, and available evidence.
- Translate research findings into practical recommendations for AI risk identification, evaluation, monitoring, and management.
- Monitor relevant developments in Indian AI governance, standards, and regulatory frameworks and assess their implications for AI safety practices.
Collaboration with AI Safety Testing & Evaluation
- Work closely with the AI Safety Research & Testing Professional to interpret technical evaluation findings.
- Analyse testing results in the context of existing AI safety research, frameworks, and standards.
- Identify recurring failure modes, emerging risks, and research questions based on empirical testing.
- Contribute to documenting and communicating findings from AI model and product evaluations.
- Help identify areas where additional testing or research may be required.
- Support the development of research outputs that combine empirical evaluation results with broader AI safety evidence.
Knowledge Sharing & External Engagement
- Contribute to workshops, briefings, roundtables, and knowledge-sharing activities on AI safety and security.
- Support engagement with industry, research, and other relevant partners.
- Present research findings and analysis to technical and non-technical audiences.
- Represent the initiative at relevant conferences, working groups, and technical or policy discussions, as appropriate.
- Build and maintain awareness of the wider AI safety research ecosystem and relevant organisations.
- Support the development of educational and awareness materials related to AI safety and security.
Required Qualifications
- 2-3 years of relevant experience in AI/ML research, AI safety, technology policy, AI governance, cybersecurity, technology risk, responsible AI, research, or a closely related field.
- Strong research and analytical capabilities, with demonstrated ability to identify, assess, and synthesise information from multiple sources.
- Strong written and verbal communication skills, with the ability to produce clear, structured, and evidence-based research outputs.
- Working understanding of modern AI/ML systems, including large language models, foundation models, fine-tuning, RAG, and agentic AI systems.
- Good conceptual understanding of AI safety and security risks and emerging AI evaluation approaches.
- Ability to read and understand technical AI research papers, evaluation reports, and related documentation.
- Ability to distinguish established evidence from emerging research, assumptions, and areas of uncertainty.
- Strong attention to detail and commitment to evidence-based analysis.
- Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Cybersecurity, Public Policy, Technology Policy, or a related discipline. A Master's degree or relevant research experience is a strong plus.
Preferred / Nice-to-Have
- Familiarity with AI safety research, AI evaluations, alignment, interpretability, robustness, AI assurance, or related areas.
- Familiarity with AI governance frameworks, standards, and emerging regulatory developments.
- Experience researching AI safety, cybersecurity, technology risks, or responsible AI.
- Familiarity with research and publications from AI Safety Institutes, evaluation labs, standards organisations, or leading AI research organisations.
- Experience producing research reports, policy briefs, technical papers, landscape assessments, or similar analytical outputs.
- Experience working with AI governance, responsible AI, technology risk, assurance, or compliance programmes.
- Basic technical skills in Python, data analysis, or AI evaluation are an advantage but are not essential.
- Public research, writing, or open-source contributions related to AI, AI safety, cybersecurity, or technology policy are a plus.
- Participation in AI safety programmes, fellowships, research groups, or relevant professional communities is a plus.
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