NVIDIA is building a Taiwan-based team, working with counterparts in the United States, to support CPU programs. This team will provide in-person and in-time-zone support for NVIDIA platform factories and ODM/OEM partner factories. The Technical Delivery Lead will address SBIOS issues reported by customers, partners, ODMs, and internal stakeholders. The role calls for a firmware or embedded engineer who can work across varied code bases and modules, solve problems directly, and engage domain experts when needed.
What you'll be doing:
Provide in-person and in-time-zone support for NVIDIA platform factories and ODM/OEM partner factories.
Develop, triage, and debug ARM/RISC-V chip-level firmware.
Investigate and resolve the majority of reported issues independently across diverse code bases and modules, engaging domain experts when needed.
Leverage AI to accelerate analysis, exploration, and documentation while maintaining the rigor, originality, and engineering judgment required to validate results.
What we need to see:
B.S. degree or equivalent experience in Computer Science, Electrical Engineering, Computer Engineering, or a related field.
8+ years of firmware and embedded systems engineering experience.
Proven ability to work across diverse code bases and modules to solve complex technical problems.
Strong problem-solving skills with the ability to work independently and collaborate effectively with domain experts.
Ways to stand out from the crowd:
Demonstrated experience using AI as a core part of the engineering workflow to:
Develop tools that help diagnose and resolve SBIOS issues.
Accelerate problem analysis and exploration across diverse code bases.
Apply sound judgment to determine when AI-generated output should be trusted, verified, or overridden.
Share effective AI tools, prompts, and best practices with fellow engineers.
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the most desirable employers in the world. We have some of the most brilliant and talented people in the world working for us. If you are creative, autonomous and love a challenge, we want to hear from you. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Skills Required
- Bachelor's degree or equivalent experience in Computer Science, Electrical Engineering, Computer Engineering, or a related field
- 8+ years of firmware and embedded systems engineering experience
- Experience working across diverse codebases and modules to solve complex technical problems
- Strong problem-solving skills and ability to work independently and collaborate with domain experts
- Experience using AI in engineering workflows to diagnose issues, accelerate analysis, and evaluate AI-generated output
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.
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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.
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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.
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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.”
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