Adversarial Machine Learning Engineer - Red Teaming

📋 Description Conduct hands-on adversarial testing across AI models, apps, agentic systems, and data pipelines to Perform red-team assessments: jailbreaks, guardrail bypass, prompt injection, tool-chain misuse Investigate edge-case findings and convert them into reproducible vulnerabilities. Assess risks like data poisoning, model inversion, membership inference, model extraction. Align security evals with OWASP Top10 for LLMs, NIST AI RMF, MITRE ATLAS, AI regs. Produce vulnerability reports with severity, evidence, steps, remediation tips. 🎯 Requirements Expert-level Python with PyTorch, TensorFlow, and Hugging Face Transformers. Hands-on fine-tuning of ML models/SLMs; LoRA, QLoRA, PEFT, instruction tuning, domain adaptation. Strong ML math: optimization, linear algebra, probability, statistics. Experience designing adversarial ML attacks: data poisoning, model extraction, membership inference. Experience building AI security defenses: adversarial training, robust fine-tuning, input Familiarity with Adversarial Robustness Toolbox, CleverHans, Foolbox. 🎁 Benefits Fully remote position available anywhere in Canada. Flexible environment focused on outcomes and impact. Work on advanced AI security challenges with foundation models. Clear career growth toward staff/principal-level influence. Supportive hiring process with guidance beyond. Collaborate with experienced AI security professionals.