Senior Linux System Software Engineer (Tegra) - Edge AI

NVIDIA Corporation; Santa Clara (CA); On-site; USD 184,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits package

Competitive salary

Job summary

NVIDIA is seeking a senior software engineer to advance power and thermal management on Tegra SoCs and embedded platforms. You will design and implement Linux kernel and user-space features, collaborating across hardware and software teams to optimize energy use and performance for edge AI workloads.

The role requires strong C skills, Linux kernel experience, and embedded ARM expertise, with opportunities for impact across AI computing and autonomous edge devices.

Qualifications

• MS in CS, CE, EE, Systems Engineering or related field, or equivalent experience.
• 8+ years of software development with a significant focus on Linux.
• Proficient in C programming and debugging in Linux kernel and user space software.
• Experience with embedded systems and ARM processor architectures.
• Strong system-level debugging and problem-solving skills.
• Excellent communication skills.

Responsibilities

• Develop power and thermal management features for Linux Kernel and user space.
• Collaborate with power architects, hardware and software engineers on platform power estimation and optimization.
• Optimize software to improve performance, efficiency, and edge AI workloads.
• Tune system-level performance for reliable, scalable edge environments.

Skills

Linux kernel programming

C programming

Embedded systems

ARM architecture

System-level debugging

Communication skills

Education

MS in CS, CE, EE, Systems Engineering or related

Tools

GCC

Linux kernel debugging tools

Open-source tooling

Job description

NVIDIA is seeking a senior software engineer to advance power and thermal management on Tegra SoCs and embedded platforms. You will design and implement Linux kernel and user-space features, collaborating across hardware and software teams to optimize energy use and performance for edge AI workloads.

The role requires strong C skills, Linux kernel experience, and embedded ARM expertise, with opportunities for impact across AI computing and autonomous edge devices.