Job description

NVIDIA is leading the industry in delivering accelerated computing in cloud and enterprise environments. We’re a team of innovative engineers dedicated to solving some of the world’s biggest challenges, constantly driving advancements, and impacting millions of lives worldwide! As a technology leader at NVIDIA, you will lead the development of our global strategy for scaled-out AI inferencing. You will architect the high-throughput, low-latency distributed pipelines and model serving strategies required for massive scale and production reliability. You will define and drive the technical roadmap for full-lifecycle, from deployment and versioning to automated scaling, across enterprise and cloud environments. Working with NVIDIA leadership, you will establish the systems and orchestration layers that enable the world’s most advanced AI models to run with peak efficiency on our accelerated computing hardware. What You’ll Be Doing: • Various Architectural Work: Architect distributed pipelines, define and drive the technical implementation of high-throughput, low-latency, distributed inference systems to support massive-scale AI workloads. • Collaborate on Cross Domain Disciplines: Hardware-software co-optimization, drive performance tuning at the kernel and driver level, optimizing GPU resource management and hardware acceleration for production-grade model serving. • Collaborate on Open Source and Ecosystem Projects: Guide and influence open source projects Dynamo, TensorRT-LLM, and ecosystem projects (vLLM, SGLang, Linux, Kubernetes, Ray) to bring state of the art inferencing on NVIDIA accelerated hardware. • Accelerate Integration: Orchestrate model lifecycles, lead the strategy for full-lifecycle model management, including automated deployment, versioning, and intelligent scaling across varied cloud and datacenter environments. • Engage Stakeholders: Collaborate with customers, infrastructure providers, and partners to ensure NVIDIA’s solutions set the industry standard for performance and availability. • Full Software and System Lifecycle: From ideation to architecture, design, development, deployment, operations, and full lifecycle management, lead all technical aspects of planning and continuous evolution of a large technical scope. What We Need to See: • 16+ overall years in technical roles with a recent long-term focus on AI infrastructure and more recent direct experience in large-scale inference orchestration. Proven track record building secure, highly available, and durable production distributed systems. • 7-10+ years of leadership experience • BS/MS or higher or equivalent experience in systems / software engineering, or related engineering fields • Deep Technical Expertise: Proficiency in GPU architecture, hardware acceleration, and low-level performance tuning (CUDA, kernels) alongside cloud-native architectures for multi-tenant model serving. • Proven success delivering high-impact technically complex solutions that achieve high levels of transparency into resource utilization, performance, and operational insights. • Technical Leadership: Develop and advance consensus and organizational alignment across technical leadership and the highest level of senior corporate leadership. Ability to synthesize cross-functional needs into architecture and design while guiding internal execution across diverse teams. • Communication and Teamwork: Strong collaboration and influence skills, capable of leading engineering engagement, communicating with peers, partners, and working with high performance and accelerated computing customers. Ways to Stand Out from the Crowd: • Application of Artificial Intelligence: Real world experience building the systems to support AI/ML workloads. • Industry Expertise: Direct experience in designing, developing, delivering and operating secure, highly available, scaled out systems in enterprise and cloud environments. • Engineering Enablement: Demonstrated history of creating scalable processes and extensible systems that facilitate cross-functional collaboration and operations at scale. • Open Source Collaboration: Familiarity with open source ecosystems and projects (e.g. Dynamo, TensorRT-LLM, vLLM, SGLang, Ray). Ability to collaborate and influence in open source project governance to represent NVIDIA, customers, and partners interests in technical alignment and direction. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative, passionate and self-motivated, we want to hear from you! With competitive salaries and a generous benefits package ( www.nvidiabenefits.com ), we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 320,000 USD - 488,750 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until August 15, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive 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.

Requirements

Must-haves

Various Architectural Work: Architect distributed pipelines, define and drive the technical implementation of high-throughput, low-latency, distributed inference systems to support massive-scale AI workloads.
Engage Stakeholders: Collaborate with customers, infrastructure providers, and partners to ensure NVIDIA’s solutions set the industry standard for performance and availability.
7-10+ years of leadership experience
BS/MS or higher or equivalent experience in systems / software engineering, or related engineering fields
Deep Technical Expertise: Proficiency in GPU architecture, hardware acceleration, and low-level performance tuning (CUDA, kernels) alongside cloud-native architectures for multi-tenant model serving.
Proven success delivering high-impact technically complex solutions that achieve high levels of transparency into resource utilization, performance, and operational insights.
Communication and Teamwork: Strong collaboration and influence skills, capable of leading engineering engagement, communicating with peers, partners, and working with high performance and accelerated computing customers.
Application of Artificial Intelligence: Real world experience building the systems to support AI/ML workloads.
Industry Expertise: Direct experience in designing, developing, delivering and operating secure, highly available, scaled out systems in enterprise and cloud environments.
Engineering Enablement: Demonstrated history of creating scalable processes and extensible systems that facilitate cross-functional collaboration and operations at scale.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until August 15, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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