Senior System Software Engineer, GPU Power Management

Nvidia

Confirmed live yesterday High trust

Quick summary

Work type
Remote
Location
Remote
Salary
$224,000–$356,500 / yr
Employment
Full-time
Posted
13 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $213k
This role $290k
$143k most similar roles pay here $379k

This role pays more than 98% of similar roles. Most pay $190,750–$235,750 — the shaded band above. At the midpoint, this role pays about $290k versus about $213k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1371 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1096 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior System Software Engineer, GPU Power Management

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As a Senior System Software Engineer - GPU Power Management, you will join the GPU Performance and Power Management Software team to architect and develop production software for performance states, power management controllers, and dynamic voltage and frequency scaling for next-generation data-center GPUs. You will build real-time controllers, policies, and mechanisms that optimize performance, thermals, and energy efficiency while managing complex interactions between workloads, clocks, voltages, and system-level policies. The role involves the full product lifecycle, from pre-silicon validation to silicon bring-up and production support. You will utilize C to develop low-level software, firmware, and device drivers. Key requirements include expertise in operating-system fundamentals, concurrency, interrupt handling, and hardware programming. This position addresses critical power management challenges at the intersection of hardware architecture, embedded systems, and high-demand data-center workloads to ensure reliability and efficiency.

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