Adversarial Machine Learning Engineer - Red Teaming
RemoteCanada
CanadaRemoteFull TimeSmall
Full TimeSmall
Job Summary
Conduct hands-on adversarial testing across the model, application, and data pipeline, executing multi-turn jailbreaks, prompt injections, and dangerous-capability evaluations. Dig deeper into edge-case findings from AI red-team campaigns to turn flagged anomalies into reproducible vulnerabilities mapped to OWASP, NIST, and EU AI Act standards. Provide remediation guidance and lead retests to confirm fixes hold. Translate technical depth into plain language for engineers and stakeholders while staying embedded through the entire remediation cycle. Collaborate shoulder-to-shoulder with the client's Guardrails and AI red-teaming team.
Required Qualifications
- Expert-level Python programming with deep proficiency in ML frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers
- Hands-on experience fine-tuning ML models and Small Language Models (SLMs) — including techniques such as LoRA/QLoRA, PEFT, instruction tuning, and domain adaptation — for both performance and robustness objectives
- Strong foundation in ML mathematics: optimization, linear algebra, probability, and statistics
- Proven ability to design and execute adversarial attacks, including evasion (adversarial examples), data poisoning, model extraction, and membership inference
- Experience implementing defenses such as adversarial training, robust fine-tuning, input sanitization, and differential privacy
- Proficiency with adversarial ML toolkits such as Adversarial Robustness Toolbox (ART), CleverHans, and Foolbox
- Experience red-teaming AI/LLM systems, including prompt injection, jailbreak testing, and safety/alignment evaluation
- Ability to evaluate and benchmark model robustness, safety, and security posture before and after fine-tuning
- Familiarity with MLOps practices — model versioning, experiment tracking, and secure deployment pipelines
- Strong threat-modeling skills and an attacker's mindset, with the ability to communicate risks clearly to technical and non-technical stakeholders
- Active awareness of the latest adversarial ML and GenAI security research
Desired Qualifications
- Experience with Guardrails and AI red teaming for foundation model suites
- Ability to design and train ML models as well as SLM's in the security context
- Ability to design and train ML models as well as SLM's in the security context
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