Adversarial Machine Learning Engineer
AI Summary
An adversarial machine learning engineer develops and tests AI systems to identify vulnerabilities, jailbreaks, data exfiltration attempts, and guardrail bypasses, and creates tooling for automated attack scenarios.
About this role
The Opportunity
We are building a dedicated AI Red Team to rigorously test and harden enterprise-scale AI products.
We are looking for an adversarial machine learning specialist who thinks like an attacker.
This role focuses on identifying vulnerabilities in LLM-driven systems, breaking model guardrails, exploiting data pathways, and stress-testing AI deployments before they reach enterprise customers.
This is a hands-on technical role at the core of AI security.
What You’ll Do
- Conduct adversarial testing across LLM and AI-based systems
- Execute real-world attack simulations, including:
- Prompt injection
- Jailbreaking and guardrail bypass
- Data exfiltration attempts
- Model inversion and evasion techniques
- RAG manipulation
- Develop scripts and tooling to automate attack scenarios
- Analyse model behaviour under adversarial pressure
- Identify systemic vulnerabilities in:
- APIs
- Embedding pipelines
- Vector databases
- Fine-tuned model implementations
- Collaborate with engineering teams to validate remediation
- Document findings clearly and concisely
You will help ensure AI systems are resilient before they are deployed at scale.
Requirements
What We’re Looking For
Core Technical Skills
- Strong experience in adversarial ML or AI security research
- Experience working with LLM-based systems (OpenAI, Anthropic, open-source models, etc.)
- Deep understanding of:
- Prompt injection techniques
- Model jailbreak methodologies
- AI system exploitation vectors
- Strong Python skills
- Experience building custom attack tooling or experimentation frameworks
AI Systems Knowledge
-
Familiarity with:
- RAG architectures
- Vector databases
- Model fine-tuning workflows
- API-based model deployments
- Understanding of model safety mechanisms and guardrails
Nice to Have
- Background in cybersecurity or penetration testing
- Familiarity with OWASP LLM Top 10
- Experience working in enterprise environments
Who You Are
- Curious and relentless
- Comfortable thinking like an attacker
- Creative in finding non-obvious vulnerabilities
- Detail-oriented but fast-moving
- Comfortable operating in ambiguity
- Independent but collaborative
You don’t just run test cases — you design new ones.
Benefits
- Comprehensive Private Medical Coverage
- Support for Mental Health Expenses
- Life Insurance Options
- Attractive Compensation Package
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