A.I. Adversarial Testing and Vulnerability Specialist

5 days ago

Toronto, Ontario, Canada The Toronto-Dominion Bank (Canada) Full time

Job Description

At The Toronto-Dominion Bank (Canada), we are seeking an A.I. Adversarial Testing and Vulnerability Specialist to join our team. As an A.I. Adversarial Testing and Vulnerability Specialist, you will be responsible for developing and implementing test tools that evaluate the resilience of A.I.-enabled systems to adversarial attacks.

Responsibilities

  • Evaluate the security of A.I. models, A.I.-enabled systems, and operationally realistic scenarios through red teaming exercises.
  • Develop and maintain tools, scripts, and frameworks to automate the evaluation and resilience of A.I.-enabled systems to adversarial attacks.
  • Collaborate with industry subject matter experts to identify potential threats and vulnerabilities and create test tools that assess their impact and likelihood.
  • Work on solutions to enhance defense mechanisms, such as anomaly detection, intrusion detection systems, and threat intelligence for A.I. models.
  • Generate comprehensive reports and documentation of red teaming exercises, including findings, vulnerabilities, and recommendations for remediation.
  • Stay up-to-date with the latest advancements in A.I. to continuously improve attack techniques and defense strategies.
  • Collaborate with cross-functional teams, including cybersecurity experts, A.I. model developers, A.I. model users, and test engineers, to provide insights and recommendations for improving A.I. defenses.

Requirements

  • Bachelor's or Master's degree in computer science, computer engineering, or a relevant field.
  • Minimum 5+ years of experience in IT, with 2+ years in A.I., 3+ years in Azure Cloud Engineering, and 3+ years in adversary experience.
  • Strong programming skills, especially in languages like Python and C++.
  • Proficiency in machine learning and A.I. technologies.
  • Experience with evaluating A.I. models and creating test harnesses for offensive use.
  • In-depth knowledge of A.I. adversarial concepts, threats, and defensive measures.
  • Experience with penetration testing and ethical hacking.
  • Familiarity with A.I. and cybersecurity frameworks and standards (e.g., NIST, MITRE ATT&CK, MITRE ATLAS).
  • Experience with Model Evasion, Extraction, Inversion, Poisoning attacks, and LLM Prompt injection.
  • Strong communication skills to articulate findings and recommendations effectively.
  • Demonstrated expertise in A.I. threat landscapes.
  • Experience with Enterprise Data Lakes, relational databases, complex data structures, data analysis tools.

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