Software Application Engineer – SoC Platform

Reposted 7 Days Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
108K-213K Annually
Mid level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Develop software design guides, diagnostic tools, and optimize platform features while collaborating with hardware teams and OEM partners for notebook systems.
Summary Generated by Built In

We are seeking an experienced Software Application Engineer to collaborate with NVIDIA and ecosystem partners, driving next-generation notebook platforms through advanced software design, diagnostics, and embedded controller expertise. The role encompasses delivering design guides, tuning and qualification tools, and optimizing modern standby and battery life, with full support for OEM debug and testing.

What you’ll be doing:

  • Develop and maintain software design guides, diagnostic utilities, high-speed IO tuning and qualification tools for notebook platforms.

  • Collaborate with hardware and software engineering teams at NVIDIA and partner organizations to enable system features and resolve technical issues.

  • Lead embedded controller (EC) and PMIC bring-up, debugging, and feature enablement for new notebook designs; provide technical solutions for EC firmware issues and validation.

  • Work directly with OEM/ODM partners to support debug, issue triage, and system testing for platform integration and compliance.

  • Design and optimize modern standby features, driving improvements in sleep, resume, power efficiency, and battery life.

  • Own software tool development for high-speed IO performance, compliance, and system qualification.

  • Participate in validation planning and troubleshooting for system and application defects at both firmware and software levels.

What we need to see:

  • BS/MS in Computer Science, Electrical Engineering, or related field (or equivalent experience)

  • 3+ years’ experience in software/platform engineering for notebooks, embedded controllers, or application/tool development.

  • Strong hands-on skills in coding, debug, and troubleshooting for embedded controller and SBIOS.

  • Experience supporting OEM customers in technical debug, testing, and integration.

  • Familiarity with modern standby, notebook power management, and Windows platform features.

  • Track record of multi-functional collaboration with silicon vendors (NVIDIA or similar) and OEM/ODM partners.

Ways to stand out from the crowd:

  • Any CUDA or driver experience with NVIDIA products under Linux and Windows

  • Familiarity with scripting languages such as bash, Ruby or Python.

  • Any exposure to system level debug and triage experience

  • BIOS engineer experience for 2+ years.

  • Experience with ARM as well as experiences in SBIOS features developing specific platforms. (MMIO, SMBus, IPMI, IOAPIC will be plus)

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 218,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until January 13, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

Top Skills

Bash
Embedded Controllers
Nvidia
Python
Ruby
Sbios
Windows
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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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