NVIDIA is widely considered to be one of the technology world’s most desirable employers with some of the most innovative engineers and technologists. We are seeking system safety engineers to lead efforts developing the next generation of safe, AI-powered autonomous driving systems. In this role, you will focus on applying V-Model methodologies to cross-disciplinary development across AI, computer vision, software architecture, planning and control, software / hardware interactions. You will be part of a team that covers the entire autonomous driving system and coordinates development teams across NVIDIA.
What you’ll be doing:
Work closely with diverse teams of engineers to derive functional and safety requirements from use cases and driving modes on the left side of the V-Model, and to integrate and validate requirements on the right.
Contribute to architecture decomposition and architecture validation, and will teach and mentor the development teams in requirements process, work flow and good requirements composition practices.
We will count on you to guide teams in system safety engineering methodologies for development and verification.
Apply your skills to help teams with requirements traceability, verification methodologies for safety, manage conflicting and changing requirements, and establish and manage projects in JAMA.
We will look to you to collaborate with other teams within NVIDIA on V-Model process improvements, and to support alignment to customer requirement management processes.
Applying MBSE development methods to safety and security functions.
What we need to see:
BS, MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience
8+ years of proven industry experience.
We are looking for technically strong engineers with a hands-on approach to systems engineering, candidates who enjoy teaching and helping teams.
Strong written and verbal communication skills. and engineers who thrive working in teams and across multiple domains.
Bring a keen eye reviewing existing processes and finding gaps to suggest improvements.
We seek engineers who bring experience in process definition, improvement, implementation, and roll-out.
Ways to stand out from the crowd:
We enjoy seeing strong backgrounds in these areas
Proven hands-on experience with state-of-the-art systems engineering methodologies – such as requirements management, peer review processes, configuration management, requirements management in an agile development environment, risk management, requirements verification and traceability, validation and verification, and architectural decomposition
Success applying the V-Model to complex engineering projects, ideally in all stages of the SW development life cycle
Hands-on experience in ADAS or autonomous vehicle systems as well as practical experience in applying Model Based System Engineering (MBSE)
System safety methodologies & practices (FMEA, FTA, STPA, CPA)
Safety standards (ISO 26262, IEC 61508, ISO 21448, ISO 8800)
With competitive salaries and generous benefits packages, we are widely considered to be one of the technology world’s most desirable employers; we have some of the most forward-thinking and hardworking people in the world working for us and, due to unparalleled growth, our best-in-class teams are rapidly growing. If you're creative and passionate about safety and autonomous driving, we want to hear from you
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.
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.Skills Required
- BS, MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience
- 8+ years of proven industry experience
- Hands-on systems engineering experience with requirements derivation, verification, and architecture decomposition
- Experience applying V-Model development methodologies across software, hardware, AI, and perception domains
- Experience with requirements traceability and verification methodologies and managing projects in JAMA
- Experience applying MBSE (Model-Based Systems Engineering) to safety and security functions
- Strong written and verbal communication and mentoring/teaching skills
- Experience in process definition, improvement, implementation, and roll-out
- Practical knowledge of system safety methodologies (FMEA, FTA, STPA, CPA)
- Familiarity with automotive and functional safety standards (ISO 26262, IEC 61508, ISO 21448, ISO 8800)
- Hands-on experience in ADAS or autonomous vehicle systems
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
-
Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
-
Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
