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System Software Engineer, GPU Kernel Driver

Job in Coos Bay, Coos County, Oregon, 97458, USA
Listing for: NVIDIA
Full Time position
Listed on 2026-02-15
Job specializations:
  • Software Development
    Embedded Software Engineer, Software Engineer
Salary/Wage Range or Industry Benchmark: 241500 USD Yearly USD 241500.00 YEAR
Job Description & How to Apply Below

Employer Industry: Technology and Artificial Intelligence

Why consider this job opportunity
  • Salary up to $241,500
  • Eligible for equity and comprehensive benefits
  • Opportunity for career advancement and growth within a leading tech company
  • Work collaboratively with global teams on cutting-edge technology projects
  • Chance to contribute to innovative GPU and embedded system solutions
What to Expect (Job Responsibilities)
  • Develop and verify GPU features from initial design through deployment, collaborating with hardware and software teams
  • Lead the integration of complex system software components to deliver high-performance GPU solutions
  • Design and implement features for GPUs in collaboration with engineering teams
  • Evaluate methodologies and tools to enhance security and quality of embedded software
  • Identify vulnerabilities in production kernel and embedded software, building proof of concepts and working on solutions
What is Required (Qualifications)
  • BS or MS degree in Computer Engineering, Computer Science, or related field, or equivalent experience
  • Minimum of 2 years of industry experience in software development
  • Proficient in C programming and low-level driver experience
  • Familiarity with computer system architecture, microprocessors, and microcontroller fundamentals
  • Experience with kernel systems such as Linux, Android, Chrome, or Windows
How to Stand Out (Preferred Qualifications)
  • Familiarity with kernel-level security concepts, including testing techniques and static code analysis
  • Background in embedded system software concepts, such as RTOS and resource-constrained programming
  • Experience on virtualization platforms like Xen Server, KVM, or Hyper‑V

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