A.I. Adversarial Testing Engineer

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The Toronto-Dominion Bank (Canada)
Old Toronto
CAD 80,000 - 100,000
Be among the first applicants.
7 days ago
Job description

A.I. Adversarial Testing Engineer

Work Location: Toronto, Ontario, Canada

Hours: 37.5

Line of Business: Analytics, Insights, & Artificial Intelligence

Job Description:

Responsibilities

  • Develop and implement test tools that evaluate the resilience of an AI-enabled system to adversarial attacks.
  • Conduct red teaming exercises to assess the security of AI models, AI-enabled systems, and operationally realistic scenarios.
  • Collaborate with industry subject matter experts to identify potential threats and vulnerabilities and create test tools that assess their impact and likelihood.
  • Build and maintain tools, scripts, and frameworks to automate the evaluation and resilience of AI-enabled systems to adversarial attacks.
  • Work on solutions to enhance defense mechanisms, such as anomaly detection, intrusion detection systems, and threat intelligence for AI 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 AI to continuously improve attack techniques and defense strategies.
  • Collaborate with cross-functional teams, including cybersecurity experts, AI model developers, AI model users, and test engineers, to provide insights and recommendations for improving adversarial AI defenses.

Required skills and qualifications

  • Bachelor’s/Master’s degree in computer science, computer engineering, or relevant field
  • Minimum 5+ years in IT
    • 2+ Years in AI
    • 3+ Years Azure Cloud Engineer
    • 3+ years in Adversary experience
  • Strong programming skills, especially in languages like Python and C++.
  • Proficiency in machine learning and AI technologies.
  • Experience with evaluating AI models and creating test harness for offensive use.
  • In-depth knowledge of adversarial AI concepts, threats, and defensive measures.
  • Experience with penetration testing and ethical hacking.
  • Familiarity with adversarial AI 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 Adversarial AI threat landscape.
  • Experience with Enterprise Data Lakes, relational database, complex data structures, data analysis tools.
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