Senior Responsible AI Researcher

ActiveFence

. Lead state-of-the-art research initiatives at the intersection of frontier models, Trust & Safety, model evaluation, and adversarial robustness .

Posted 10/18/2026full-timeRemote • California • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in AI Safety, Trust & Safety, and model evaluation, with a strong foundation in Python and modern ML/DL frameworks. Proven ability to lead research initiatives, develop evaluation methodologies, and communicate complex concepts effectively to diverse stakeholders.

Highest-signal resume keywords

PhD In Science, Technology And Society StudiesAI SafetyPython ProgrammingModel EvaluationPeer-Reviewed Publications

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningDeep LearningBenchmark DesignRed-Teaming ProtocolsFoundation ModelsAdversarial PromptingData Set DesignEvaluation FrameworksMultimodal SystemsSynthetic Simulation Platforms

Soft Skills

Excellent Communication SkillsTechnical LeadershipMentorshipCollaborationResearch Initiative

Tools & Technologies

PyTorchTransformersAI Safety ToolsEvaluation SuitesAgentic Safety Gyms

Industry Keywords

Responsible AITrust & SafetyEmerging RisksBehavioral SafetyElection IntegrityPsychological ManipulationFrontier AI LabsSafety Mitigation TechniquesAI EthicsSocial Data Science

Tech Stack

Tools & technologies

PythonPyTorchGo

About the role

Key responsibilities & impact

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

What you’ll need

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)