🔥 19 hours ago
Build and ship reliable Android and iOS features for an AI neobank, turning complex financial journeys into intuitive mobile experiences while improving app performance, quality, and user experience.
Systems Security Engineer - Quantitative Risk Assessment
📅 Aug 5
Systems EngineeringCybersecurityQuantitative Risk AssessmentEPSS
📜 Description
- Quantify security-related safety risks and align assessments with safety teams and security objectives.
- Verify quantified risks by fuzzing real-world scenarios in simulator environments.
- Write design proposals, drive execution, and proactively communicate risks to partner teams.
- Identify opportunities to integrate risk metrics into company-wide frameworks.
- Collaborate across product security, software, and hardware engineering, accounting for underlying engineering constraints.
🛠️ Requirements
- Master’s degree in CS or related engineering field (software, hardware, systems) and 3+ years of experience
- A strong general systems engineering background along with a demonstrated passion and concrete expertise in cybersecurity
- Prior experience with quantitative risk assessment frameworks (eg: EPSS, Attack trees/graph quantification, Monte Carlo simulations, Bayesian networks)
- Prior experience with the risk analysis of complex embedded systems and a demonstrated skill in turning the analysis into high-quality written deliverables
- Pragmatic adoption of AI/LLM toolchains for security analysis and authoring high quality regulatory work products
- Experience with autonomous vehicle software stack (e.g., Perception, Prediction, Planning)
- Experience implementing large-scale evaluation pipelines
- Familiarity with common cloud deployment architecture and frameworks
Full job description
The Product Security team is responsible for conducting structured security analyses of Zoox products and applying security standards judiciously throughout the System Development Life Cycle at Zoox. The ideal candidate for this team will have a robust background in cybersecurity, coupled with an ability to model and quantify cybersecurity risk.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
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Accommodations
If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
In this role, you will:
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.
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.
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.
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.
Research state of the art techniques to identify, analyze and defend against cybersecurity risks for autonomous vehicles and ride hailing service.
Qualifications
PhD in Cybersecurity/CS or related engineering field (software, hardware, systems)
Strong mathematical background with strong understanding of probabilistic risk modeling and frameworks
Pragmatic adoption of AI/LLM toolchains for security analysis and authoring high quality regulatory work products
Bonus Qualifications
Prior experience with quantitative risk assessment frameworks (eg: EPSS, Attack trees/graph quantification, Monte Carlo simulations, Bayesian networks)
Prior experience with the risk analysis of complex embedded systems and a demonstrated skill in turning the analysis into high-quality written deliverables
Familiarity with common cloud deployment architecture and frameworks
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