Offensive Security Engineer, Automotive

NVIDIA Corporation
Santa Clara, CA, United States
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Compensation
$184,000.0 - $287,500.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence ARM Architecture C++ (Programming Language) Computer Programming Linux Dynamic Program Analysis Embedded Software Firmware Python (Programming Language) Reduced Instruction Set Computing Security Software Software Organization
+5 more
Multi-Agent Systems Apache Spark Information Technology Code Inspection Formal Methods

Requirements

This includes security pipelines, fuzzing infrastructure, AI-assisted vulnerability discovery, tools for automated code inspection, and code conversion. You’ll work closely with security researchers and engineers, owning tool development - from prototype to production - for use across the software organization What we need to see : + 7+ years of hands on programming experience, particularly with C/C++. Python and memory safe language (e.g. Rust, Ada/SPARK) proficiency a plus. + B.S. or equivalent experience in Computer Science or a related field. + Strong low-level systems security background: OS internals, kernels, hypervisors, firmware, or hardware; applying an analytical approach dissecting the functionality of intricate software and identifying security flaws. + Experience with embedded software engineering. Deep understanding of foundational computer science concepts and security principles. + Experience building automated security tooling: fuzzers , sanitizers, static/dynamic analysis at the source and binary level. + Knowledge of current operating system architectures and security frameworks, with a particular focus on Linux. + Proven understanding of x86 and ARM architecture . + Hands-on experience developing and building agentic AI systems: multi-agent orchestration, tool-use pipelines, and applying them to automate security or engineering workflows. Ways to stand out from the crowd : + Involvement in CTF competitions, bug bounty contributions, published security research, or personal software projects. + Extensive experience with formal methods or memory-safe languages (e.g. Ada/SPARK, Rust, TLA+, Lean) for hardening low-level code and architecture. + RISC-V knowledge is a strong plus.

Benefits & conditions

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits (https://www.nvidia.com/en-us/benefits/) . Applications for this job will be accepted at least until August 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA .

About the company

US, CA, Santa Clara Full time JR2022838 NVIDIA’s Automotive Offensive Security team believes the best defense is a good offense. Securing a sophisticated automotive operating system means finding vulnerabilities then building the tooling needed to find them at scale. We’re looking for a senior engineer who can break low-level systems and then automate the insights gained from doing so into reusable security capabilities. What you’ll be doing: You’ll discover and evaluate vulnerabilities on both source code and binaries, focusing on low-level technologies such as OS kernels, Hypervisor, boot ROMs, firmware, and hardware. More than just bug finding, you’ll develop and build automation to scale your work.

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