AI Security Researcher

CommonAI CIC

. Track key research and developments relevant to the High Assurance programme, including attacks on AI models, defences against them, and the security of the systems that serve them .

Posted 10/27/2026full-timeCambridge • United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in security research and adversarial machine learning, with a strong understanding of AI systems and their vulnerabilities. Capable of producing clear technical reports and presentations while engaging in red-teaming and threat modeling within regulated environments.

Highest-signal resume keywords

Adversarial Machine LearningRed-TeamingPython ProgrammingAI Safety ResearchInterpretability Methods

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Security ResearchOffensive SecurityVulnerability ResearchThreat ModelingAI Systems UnderstandingAttacks on AI SystemsInterpretability MethodsTechnical ReportingPenetration TestingData Poisoning

Soft Skills

Excellent Written CommunicationJudgement and ConfidenceKnowledge Sharing

Tools & Technologies

Large Language ModelsCoding AssistantsProbingSparse AutoencodersCircuit Analysis

Industry Keywords

High Assurance EnvironmentsAI Assurance StandardsISO/IEC 42001NIST AI RMFEU AI ActFinancial ServicesPublic Track Record

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Track key research and developments relevant to the High Assurance programme, including attacks on AI models, defences against them, and the security of the systems that serve them
Report on what these developments mean for the programme and Members through written briefings and presentations
Review technical decisions and directions from an attacker's point of view and propose stronger alternatives
Threat-model AI systems used in regulated settings, covering model weights, training data, inference serving, and tools and agents built on them
Red-team systems within an agreed scope and report findings through a clear disclosure process
Help develop interpretability methods for simpler models and test their limits
Share knowledge with colleagues and answer technical questions from Members

Requirements

What you’ll need

Proven experience in security research, offensive security or adversarial machine learning (e.g. red-teaming, penetration testing, vulnerability research, or attacks on ML models)
A strong understanding of how modern AI systems work, including how large language models are trained, deployed and served
Familiarity with attacks on AI systems (e.g. jailbreaks, prompt injection, data poisoning, backdoors, model extraction)
Strong Python, and the ability to build your own tools and experiments
Excellent written communication: you can turn complex technical findings into clear briefings for technical and non-technical readers
The judgement and confidence to challenge technical decisions constructively
A strong enthusiasm for using LLMs, coding assistants, and agents as core tools in your own software development process
Experience with interpretability methods (e.g. probing, sparse autoencoders, circuit analysis), or a strong interest in learning them
Experience working on software systems that operate in highly regulated or high-assurance environments (e.g. financial services)
An understanding of the latest AI safety research and active involvement in that community
Knowledge of hardware and side-channel security (e.g. timing attacks, risks in shared GPU and inference infrastructure)
Familiarity with AI assurance standards and regulation (e.g. ISO/IEC 42001, NIST AI RMF, the EU AI Act)
A public track record, such as published research, CVEs, conference talks, bug bounties or CTF results
A PhD in security, machine learning or a related field, or equivalent research experience

Benefits

Comp & perks

A collaborative and supportive work environment
The opportunity to have a high impact in a growing organisation
Competitive salary package and pension
Professional development opportunities
Networking opportunities with influential people from across the tech sector, financial services, and academia
A vibrant office environment located a few minutes' walk away from Cambridge train station