Senior Responsible AI Researcher

Job not on LinkedIn

🕒 October 18

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟠 Senior

🧠 AI Research Scientist

👻 Ghost score 14%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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ActiveFence

WebsiteLinkedInAll Job Openings

201 - 500 employees

🔒 Cybersecurity

🤖 Artificial Intelligence

💰 $400M Series B on 2021-07

Cybersecurity • Artificial Intelligence

ActiveFence is a Trust and Safety provider for online platforms, protecting platforms and their users from malicious behavior and content. Trust and Safety teams of all sizes rely on ActiveFence to keep their users safe from the widest spectrum of online harms, unwanted content, and malicious behavior, including child safety and exploitation, disinformation, hate speech, terror, nudity, fraud, and more. We offer a full stack of capabilities with our deep intelligence research, AI-driven harmful content detection, and online content moderation platform. Protecting over three billion users globally everyday in over 100 languages, ActiveFence lets people interact and thrive online.

📋 Description

• Lead state-of-the-art research initiatives at the intersection of frontier models, Trust & Safety, model evaluation, and adversarial robustness • Drive self-initiated research and design evaluation methodologies for emerging risks including persuasion, manipulation, sycophancy, and agentic safety • Build safety benchmarks across Generative AI modalities: Text, Image, Multimodal, and Autonomous Agents • Serve as a key technical authority collaborating with AI labs, academic institutions, and enterprise partners • Design, build, and deploy evaluation frameworks, benchmarks, and Agentic Safety Gyms • Develop adversarial prompting methodologies, red-teaming strategies, and behavioral suites to stress-test LLMs, Multimodal systems, and AI Agents • Investigate emerging safety risks including bias and jailbreaking tactics across multimodal and autonomous architectures • Lead collaborative research projects with academic institutions and industry partners • Represent the organization at international conferences, AI safety summits, and industry events • Publish research findings in top AI and safety venues • Partner with Product, Engineering, Go-To-Market, Policy, and Delivery teams to translate research into safety products and client-facing offerings • Engage technical stakeholders and enterprise clients to translate safety and governance requirements into research questions, experiments, and evaluation suites • Provide technical leadership and mentorship to junior researchers, data scientists, and engineers • Integrate social science, policy, and technical perspectives into safety tooling and methodologies

🎯 Requirements

• PhD in Science, Technology and Society Studies (STS), Machine Learning, AI Ethics, Social Data Science, or a closely related research domain • Strong portfolio of peer-reviewed publications and conference presentations at top-tier venues (e.g., NeurIPS, ICML, ICLR, ACL, IEEE, CVPR, or dedicated AI Safety conferences) • Substantial experience in AI Safety, Responsible AI (RAI), Trust & Safety, or Model Evaluation • Strong hands-on capabilities in Python and modern ML/DL frameworks (e.g., PyTorch, Transformers) • Deep working knowledge of foundation models, including LLMs, Text-to-Image, Multimodal systems, agents, reasoning systems, and current safety mitigation techniques • Proven experience designing datasets, benchmark suites, red-teaming protocols, or synthetic simulation platforms • Proven track record of self-initiating research projects, establishing external partnerships, and shaping technical vision • Excellent verbal and written communication skills, including communicating complex technical concepts to non-technical stakeholders, executives, and research peers • Ability to work across technical data science, social science paradigms, and product execution • Prior employment, consulting, advisory, or formal research collaboration with frontier AI labs or leading safety research collectives (preferred/desirable) • Experience in domain-specific safety applications such as election integrity, psychological manipulation, or agentic behavioral safety suites (preferred/desirable)

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