In this role, you will:
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Perform Risk Assessment by quantifying security related safety risks, collaborating with cross functional teams particularly safety teams to ensure alignment with safety and security objectives while supporting risk-informed engineering decisions.
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Drive the validation and verification of quantified risk models by designing and executing automated fuzzing pipelines and edge-case scenario testing within high-fidelity simulator environments.
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Proactively identify opportunities to aggregate and integrate cybersecurity risk metrics into governance, safety, and risk management frameworks to drive strategic decision-making across the organization.
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Interface with a multitude of engineering teams within Product Security as well as across software and hardware engineering. Build and maintain a strong understanding of the underlying engineering constraints and factor that understanding into the analysis and recommendations.
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Research state of the art techniques to identify, analyze and defend against cybersecurity risks for autonomous vehicles and ride hailing service.
Qualifications
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PhD in Cybersecurity/CS or related engineering field (software, hardware, systems)
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Strong mathematical background with strong understanding of probabilistic risk modeling and frameworks
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Pragmatic adoption of AI/LLM toolchains for security analysis and authoring high quality regulatory work products
Bonus Qualifications
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Prior experience with quantitative risk assessment frameworks (eg: EPSS, Attack trees/graph quantification, Monte Carlo simulations, Bayesian networks)
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Prior experience with the risk analysis of complex embedded systems and a demonstrated skill in turning the analysis into high-quality written deliverables
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Familiarity with common cloud deployment architecture and frameworks