NVIDIA Corporation

Principal Systems Software Engineer, LPU

NVIDIA Corporation$272K — $431K *
Information Technology
11 - 15 years of experience
Job Overview by Ladders

Qualifications

  • MS in CS, CE, EE, or a related STEM field, or equivalent experience with 12+ years in production system software
  • Proficient in Rust for low-level system programming, with a proven record of shipping production software
  • Experience in designing and evolving long-term supported libraries and APIs
  • Fluency in managing large, multi-repository codebases with complex dependencies
  • Proven leadership in analyzing and resolving challenging reliability issues
  • Expertise in low-level platforms including firmware and boot processes
  • Experience in Linux drivers or adjacent kernel subsystems

Responsibilities

  • Shape architecture for hardware abstraction layers and core system libraries
  • Design and implement drivers and data movement pipelines for novel silicon
  • Build runtime interfaces for management of production-scale workloads
  • Triage and root-cause complex runtime failures
  • Lead platform bring-up in collaboration with hardware and software teams
  • Develop agent-assisted engineering practices for improved workflow
  • Communicate architectural trade-offs effectively to diverse audiences

Benefits

  • Equity participation
  • Comprehensive health benefits
  • Work-life balance initiatives
  • Opportunities for professional development
  • Collaborative and innovative work environment
Full Job Description
We are now looking for a Principal Software Engineer for LPX System Software! NVIDIA's LPX System Software team builds the foundational software that turns a novel deterministic compute architecture into a platform that compiler teams and data center operators can rely on. We shift complexity out of silicon and into software: the hardware abstraction layers, core system libraries, drivers, and runtime components that workloads enter the platform through. We build this stack in Rust. For system software living at the boundary between hardware and everything above it, we treat memory safety, explicit ownership, and long-lived API stability as the baseline rather than the goal - the foundation that lets us spend our judgment on the hard problems instead of on classes of bugs that should not exist.

As one of the principal engineers on this stack, set technical direction for the surfaces you own and shape the overall architecture alongside your fellow principals. Design the HAL, runtime interfaces, and data-movement pipelines the rest of the platform depends on; drive the hardest reliability and bring-up problems to root cause; and raise the throughput of the whole org by codifying the abstractions, patterns, and tooling that others build on. You will also help define how we engineer. We treat AI coding agents as a primary part of the workflow, and we expect our most senior engineers to be fluent in directing them - designing systems that are legible to both humans and agents, and turning hard-won judgment into leverage across the team.

What you'll be doing:
  • Shape the architecture of the hardware abstraction layers and core system libraries, and own the API contracts for the components you lead.
  • Design and implement drivers, runtimes, and data movement and aggregation pipelines that execute workloads on novel silicon.
  • Build runtime interfaces for launching, monitoring, and managing workloads at production scale.
  • Drive triage of the most difficult sequencing, initialization, and cross-component runtime failures, and produce root-cause analyses that change how the system is built.
  • Lead new platform bring-up and NPI for new boards and silicon, in tight partnership with hardware engineering, compiler teams, and data center operations.
  • Multiply the team - establish the agent-assisted engineering practices, reusable abstractions, diagnostics, and documentation that let everyone move faster without destabilizing the platform.
  • Communicate architecture and design tradeoffs clearly, in writing and in diagrams, to audiences ranging from individual engineers to executive staff.


What we need to see:
  • MS in CS, CE, EE, or a related STEM field, or equivalent experience, and 12+ years building production system software.
  • Deep systems-programming expertise, with Rust as your language of choice for low-level work. You have shipped production Rust at the hardware or kernel boundary - drivers, firmware, runtimes, or similar - and you can articulate from experience where Rust earns its keep in system software and where it costs you. We work in Rust from day one; comfort is not enough, we want conviction.
  • A track record of designing and evolving libraries and APIs meant to be supported for years, including ABI and compatibility discipline.
  • Fluency in large, multi-repository codebases with layered dependencies.
  • Demonstrated leadership driving triage of difficult reliability issues to clear, written root-cause analysis.
  • Low-level platform experience: firmware and boot flows, RTOS, BMCs/MCUs, RISC-V, or closely related system software.
  • Linux driver or kernel-adjacent experience (for example, VFIO or similar subsystems).
  • Hardware bring-up and system triage experience: fault analysis, diagnostics, and validation in lab environments.
  • An established habit: building with AI coding agents - not as a novelty, but as a way you already ship and raise leverage. You can speak to how you design work to be agent-amenable and where you keep humans in the loop.

Ways to stand out from the crowd:
  • Experience having built Rust system software at the scale of a hyperscaler or a Rust-native hardware company - the kind of environment where Rust is the production language for low-level work, not an experiment.
  • Distributed systems experience: gRPC and RPC frameworks, coordination and telemetry patterns, MPI. Inference systems and token serving experience (vLLM or similar serving and runtime stacks) a huge plus.
  • Experience shipping and supporting customer-facing SDKs, including documentation and ABI compatibility practices.
  • Production readiness and delivery depth: CI/CD and release workflows, monitoring and alerting practices, Kubernetes, and data center operational workflows.


Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 4, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

About NVIDIA Corporation

Nvidia, a global leader in graphics, gaming, and AI technology, offers Nvidia careers and internship opportunities for those passionate about driving innovation in the tech industry. you'll find a company committed to growth, teamwork, and leadership in computer science and machine learning domains.

About Nvidia

A Pioneer in Technology and Innovation

Nvidia has cemented its reputation as a powerhouse in developing advanced graphics processing units (GPUs) and has significantly contributed to the gaming industry's evolution. Moreover, its foray into AI and machine learning has opened new frontiers in technology, making Nvidia a beacon of innovation and a desirable workplace for ambitious tech professionals.

Job Opportunities

Diverse Positions in a Dynamic Field

Nvidia is continuously on the lookout for talented individuals across various domains, including hardware and software engineering, product design, marketing, and sales. Employment opportunities at Nvidia are vast, catering to a wide range of expertise and career aspirations.

Employment in Hardware and Graphics

For those fascinated by the intricacies of hardware and graphics technology, Nvidia offers positions that sit at the forefront of gaming and computing advancements.

Growth in Machine Learning and AI

Nvidia's leadership in AI and machine learning has created numerous vacancies for specialists eager to contribute to groundbreaking projects.

Recruitment in Computer Science

With the constant demand for innovation, Nvidia's recruitment efforts focus on computer science experts capable of pushing the boundaries of what's possible.

Internship Program

Opening Doors to Future Innovators

Nvidia's internship program is designed to nurture the next generation of technology leaders, offering hands-on experience in a culture that celebrates creativity and teamwork.

Benefits and Culture

Interns at Nvidia enjoy a plethora of benefits, from competitive stipends to mentorship opportunities, all within an environment that values growth and learning.

Opportunities for Students

Whether you're an undergraduate, a master's student, or a Ph.D. candidate, Nvidia's internships provide a real-world glimpse into the tech industry, offering valuable experience in various technology fields.

Pathways to Full-Time Employment

Many interns have transitioned into full-time positions, marking the start of successful careers at Nvidia. The internship program is more than a stepping stone into the company; it’s an investment in the professional development of interns. The goal is to ensure that interns are well-equipped for future challenges.

Nvidia Careers: More Than Just a Job

Nvidia offers more than just a job to its employees; it provides a front-row seat on the journey into the future of technology. Nvidia stands as a pillar of innovation with its vast opportunities in hardware, graphics, gaming, machine learning, and computer science. Nvidia careers serve as a launching pad for talented workers who aim to redefine the technological landscape. Whether through full-time positions or internships, joining Nvidia means contributing to a legacy of breakthroughs and becoming part of a global community dedicated to pushing the boundaries of what's possible.
Learn more about NVIDIA Corporation
Size
22,473 employees
Market Cap
$350.4 billion
Industry
Net Income
$4.3 billion
Founded
1993
5 Year Trend
+31.3%
Revenue
$16.6 billion
NASDAQ

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