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We are looking for an experienced and highly motivated software professional to work on pioneering initiatives and projects at the intersection of CUDA and Deep Learning Systems. As the complexity and scale of artificial intelligence continue to grow, the intersection of advanced deep learning architectures, massive-scale distributed computing, and low-level hardware optimization has never been more critical. Our team is dedicated to exploring and prototyping next-generation ideas that bridge the gap between deep learning algorithms and CUDA, pushing the boundaries of what is possible on modern accelerator architectures. Join our dynamic, research-oriented team to help unlock maximum hardware performance for emerging AI workloads. You will be a crucial member of a highly technical group exploring uncharted territories in model optimization, custom kernel development, and cluster-scale AI systems design. If you are passionate about the fundamentals of deep learning and thrive on squeezing every ounce of performance out of advanced computing systems from a single GPU to supercomputer clusters, we want you on our team! What you will be doing: Explore, research, and prototype novel systems optimizations for advanced deep learning models at the intersection of high-level DL frameworks and low-level CUDA through modeling, simulation, and silicon prototyping. Architect and optimize distributed computing systems that scale seamlessly from a single node to massive, cluster-scale supercomputing environments. Design, implement, and optimize custom high-performance CUDA kernels tailored to emerging neural network architectures and workloads. Analyze complex hardware-software interactions to identify and resolve performance bottlenecks in both training and inference pipelines. Collaborate closely with AI researchers, HW and SW architects, kernel and compiler authors and CUDA driver experts to co-design systems and algorithms that improve accelerator compute utilization, memory bandwidth, cross-node network communication efficiency and programmability. Develop exploratory tools and runtime systems to profile and accelerate new paradigms in deep learning. Write clean, effective, and maintainable code, ensuring exploratory prototypes can smoothly transition into open-source releases, upstream framework integrations, internal tools, or closed-source commercial products. What we need to see: BS, MS, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience). 2+ years of relevant industry experience or equivalent academic experience after degree achievement. Strong proficiency in C++ and Python programming. Solid background in the fundamentals of Deep Learning with a focus on transformers. Strong understanding of distributed computing principles, multi-node scaling, and the unique performance challenges of cluster-scale execution. Proven experience in systems programming, computer architecture, and low-level systems performance optimization. Familiarity with deep learning accelerator architectures such as the GPU and hands-on experience with CUDA programming, kernel optimization, and workload profiling Experience profiling and optimizing generative AI models, including but not limited to, pioneering large language models. Research background in machine learning systems or adjacent fields and experience profiling and optimizing innovative vision models, generative AI architectures, or diffusion models. A track-record of initiative and willingness to deep-dive on problems across the stack. Ways to stand out from the crowd: Deep expertise in performance internals and execution graphs of major deep learning training and inference frameworks (e.g., PyTorch, JAX, TensorRT, vLLM, sgLang, Nemo, Megatron). Hands-on experience with communication libraries (e.g., NCCL, MPI, UCX) and distributed machine learning techniques (e.g., pipeline, tensor, expert parallelism). Knowledge of numerical methods and low-precision arithmetic (e.g., NVFP4, MXFP4, FP8, INT8) and their impact on deep learning accuracy and performance. Background in deep learning compilers and ML systems, including graph-level and codegen tools (e.g., Triton, XLA, torch.compile) and highly parallel/RL-style simulation environments. Experience designing and implementing agentic AI systems applied to complex systems and infrastructure problems. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 3, 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.

We are looking for an experienced and highly motivated software professional to work on pioneering initiatives and projects at the intersection of CUDA and Deep Learning Systems. As the complexity and scale of artificial intelligence continue to grow, the intersection of advanced deep learning architectures, massive-scale distributed computing, and low-level hardware optimization has never been more critical. Our team is dedicated to exploring and prototyping next-generation ideas that bridge the gap between deep learning algorithms and CUDA, pushing the boundaries of what is possible on modern accelerator architectures. Join our dynamic, research-oriented team to help unlock maximum hardware performance for emerging AI workloads. You will be a crucial member of a highly technical group exploring uncharted territories in model optimization, custom kernel development, and cluster-scale AI systems design. If you are passionate about the fundamentals of deep learning and thrive on squeezing every ounce of performance out of advanced computing systems from a single GPU to supercomputer clusters, we want you on our team! What you will be doing: Explore, research, and prototype novel systems optimizations for advanced deep learning models at the intersection of high-level DL frameworks and low-level CUDA through modeling, simulation, and silicon prototyping. Architect and optimize distributed computing systems that scale seamlessly from a single node to massive, cluster-scale supercomputing environments. Design, implement, and optimize custom high-performance CUDA kernels tailored to emerging neural network architectures and workloads. Analyze complex hardware-software interactions to identify and resolve performance bottlenecks in both training and inference pipelines. Collaborate closely with AI researchers, HW and SW architects, kernel and compiler authors and CUDA driver experts to co-design systems and algorithms that improve accelerator compute utilization, memory bandwidth, cross-node network communication efficiency and programmability. Develop exploratory tools and runtime systems to profile and accelerate new paradigms in deep learning. Write clean, effective, and maintainable code, ensuring exploratory prototypes can smoothly transition into open-source releases, upstream framework integrations, internal tools, or closed-source commercial products. What we need to see: BS, MS, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience). 2+ years of relevant industry experience or equivalent academic experience after degree achievement. Strong proficiency in C++ and Python programming. Solid background in the fundamentals of Deep Learning with a focus on transformers. Strong understanding of distributed computing principles, multi-node scaling, and the unique performance challenges of cluster-scale execution. Proven experience in systems programming, computer architecture, and low-level systems performance optimization. Familiarity with deep learning accelerator architectures such as the GPU and hands-on experience with CUDA programming, kernel optimization, and workload profiling Experience profiling and optimizing generative AI models, including but not limited to, pioneering large language models. Research background in machine learning systems or adjacent fields and experience profiling and optimizing innovative vision models, generative AI architectures, or diffusion models. A track-record of initiative and willingness to deep-dive on problems across the stack. Ways to stand out from the crowd: Deep expertise in performance internals and execution graphs of major deep learning training and inference frameworks (e.g., PyTorch, JAX, TensorRT, vLLM, sgLang, Nemo, Megatron). Hands-on experience with communication libraries (e.g., NCCL, MPI, UCX) and distributed machine learning techniques (e.g., pipeline, tensor, expert parallelism). Knowledge of numerical methods and low-precision arithmetic (e.g., NVFP4, MXFP4, FP8, INT8) and their impact on deep learning accuracy and performance. Background in deep learning compilers and ML systems, including graph-level and codegen tools (e.g., Triton, XLA, torch.compile) and highly parallel/RL-style simulation environments. Experience designing and implementing agentic AI systems applied to complex systems and infrastructure problems. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 3, 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.

NVIDIA is powering the world’s most advanced AI factories, where resilient infrastructure is essential to keep accelerated computing environments running at scale. The Agentic AIOps team is building a mission-critical observability and prediction platform - delivered as both a high-scale SaaS solution and a robust on-premises deployment for NVIDIA’s largest enterprise customers. As a Senior DevOps Engineer, you’ll help turn agentic AI capabilities for diagnosing and troubleshooting network and GPU infrastructure into secure, scalable, production-ready services. This role stands out through its end-to-end ownership across cloud and customer-managed environments, close partnership with software and AI engineers, and direct influence on the reliability of NVIDIA’s AI infrastructure. What You'll Be Doing: Own the DevOps, infrastructure, security, release, and reliability lifecycle - from development environments and CI/CD through deployment, production readiness, and sustained operations. Build and operate Kubernetes environments and Helm-based deployments for a Python, FastAPI, Node.js, and React microservices platform across SaaS and on-premises footprints. Engineer GitLab CI/CD pipelines with automated testing, container builds, vulnerability scanning, and versioned image and Helm chart publication through JFrog Artifactory. Automate infrastructure provisioning, configuration, upgrades, and routine operational workflows to accelerate delivery and improve engineering productivity. Operate PostgreSQL, Temporal workflow services, and S3-compatible object storage with disciplined capacity planning, backups, recovery testing, and safe migrations. Strengthen release reliability through deployment validation, reduced-downtime strategies, persistent-state protection, and recovery plans for active workflows. Deliver actionable observability and security using OpenTelemetry, Datadog/Grafana, Langfuse, secrets management, identity integration, TLS, Kubernetes RBAC, network policies, and container hardening. Partner with software and AI engineers to troubleshoot distributed systems, investigate incidents, define reliability targets, and improve platform performance, resource efficiency, and customer outcomes. What We Need to See: Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent experience. 5+ years of experience in DevOps, site reliability engineering, or platform engineering supporting distributed applications and microservices. Strong hands-on experience with Kubernetes, Docker, and Helm, including networking, storage, workload scheduling, scaling, and troubleshooting. Strong Linux administration skills and proficiency in Python and Bash for automation, plus experience with infrastructure as code and configuration tooling such as Terraform and Ansible. Experience building and maintaining CI/CD pipelines, including runners, container registries, artifact management, automated quality gates, and secure release practices. Practical experience operating PostgreSQL or comparable relational databases, including SQL, migrations, backup and restore, and performance troubleshooting. Strong networking and observability fundamentals across TCP/IP, DNS, HTTP, TLS, load balancing, ingress, metrics, logs, traces, dashboards, and actionable alerting. Sound understanding of secure infrastructure operations and incident response, with demonstrated ownership, cross-functional collaboration, and prioritization in an evolving environment. Ways To Stand Out From the Crowd: Experience operating AI applications, agent platforms, or LLM services, including monitoring latency, failures, token usage, and cost. Familiarity with Temporal, LangGraph, Model Context Protocol (MCP), Langfuse, ClickHouse, Redis/Valkey, or S3-compatible storage. Deep experience with OpenTelemetry instrumentation and collectors, Datadog APM, or Prometheus/Grafana. Experience with self-hosted Kubernetes, OpenShift, Kubernetes operators, CloudNativePG, or GPU clusters and AI data centers. Experience building reproducible AMD64 and ARM64 container images, optimizing BuildKit pipelines, and securing the software supply chain. With competitive salaries and a generous benefits package, NVIDIA is 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. If you are passionate about building mission-critical systems at the frontier of AI infrastructure, we want to hear from you. #LI-Hybrid

NVIDIA is powering the world’s most advanced AI factories, where resilient infrastructure is essential to keep accelerated computing environments running at scale. The Agentic AIOps team is building a mission-critical observability and prediction platform - delivered as both a high-scale SaaS solution and a robust on-premises deployment for NVIDIA’s largest enterprise customers. As a Senior DevOps Engineer, you’ll help turn agentic AI capabilities for diagnosing and troubleshooting network and GPU infrastructure into secure, scalable, production-ready services. This role stands out through its end-to-end ownership across cloud and customer-managed environments, close partnership with software and AI engineers, and direct influence on the reliability of NVIDIA’s AI infrastructure. What You'll Be Doing: Own the DevOps, infrastructure, security, release, and reliability lifecycle - from development environments and CI/CD through deployment, production readiness, and sustained operations. Build and operate Kubernetes environments and Helm-based deployments for a Python, FastAPI, Node.js, and React microservices platform across SaaS and on-premises footprints. Engineer GitLab CI/CD pipelines with automated testing, container builds, vulnerability scanning, and versioned image and Helm chart publication through JFrog Artifactory. Automate infrastructure provisioning, configuration, upgrades, and routine operational workflows to accelerate delivery and improve engineering productivity. Operate PostgreSQL, Temporal workflow services, and S3-compatible object storage with disciplined capacity planning, backups, recovery testing, and safe migrations. Strengthen release reliability through deployment validation, reduced-downtime strategies, persistent-state protection, and recovery plans for active workflows. Deliver actionable observability and security using OpenTelemetry, Datadog/Grafana, Langfuse, secrets management, identity integration, TLS, Kubernetes RBAC, network policies, and container hardening. Partner with software and AI engineers to troubleshoot distributed systems, investigate incidents, define reliability targets, and improve platform performance, resource efficiency, and customer outcomes. What We Need to See: Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent experience. 5+ years of experience in DevOps, site reliability engineering, or platform engineering supporting distributed applications and microservices. Strong hands-on experience with Kubernetes, Docker, and Helm, including networking, storage, workload scheduling, scaling, and troubleshooting. Strong Linux administration skills and proficiency in Python and Bash for automation, plus experience with infrastructure as code and configuration tooling such as Terraform and Ansible. Experience building and maintaining CI/CD pipelines, including runners, container registries, artifact management, automated quality gates, and secure release practices. Practical experience operating PostgreSQL or comparable relational databases, including SQL, migrations, backup and restore, and performance troubleshooting. Strong networking and observability fundamentals across TCP/IP, DNS, HTTP, TLS, load balancing, ingress, metrics, logs, traces, dashboards, and actionable alerting. Sound understanding of secure infrastructure operations and incident response, with demonstrated ownership, cross-functional collaboration, and prioritization in an evolving environment. Ways To Stand Out From the Crowd: Experience operating AI applications, agent platforms, or LLM services, including monitoring latency, failures, token usage, and cost. Familiarity with Temporal, LangGraph, Model Context Protocol (MCP), Langfuse, ClickHouse, Redis/Valkey, or S3-compatible storage. Deep experience with OpenTelemetry instrumentation and collectors, Datadog APM, or Prometheus/Grafana. Experience with self-hosted Kubernetes, OpenShift, Kubernetes operators, CloudNativePG, or GPU clusters and AI data centers. Experience building reproducible AMD64 and ARM64 container images, optimizing BuildKit pipelines, and securing the software supply chain. With competitive salaries and a generous benefits package, NVIDIA is 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. If you are passionate about building mission-critical systems at the frontier of AI infrastructure, we want to hear from you. #LI-Hybrid

NVIDIA is now looking for a Senior Technical Program Manager to join our DFX engineering team and lead the software methodology programs that make our chips testable, debuggable, and manufacturable at scale — across infrastructure, implementation, verification, and silicon bring-up! 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. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence. We serve as the central program management function for NVIDIA’s VLSI Engineering organization, providing the structure and insight needed to deliver world-class silicon. We align roadmaps across all silicon product lines, enabling technical leads to focus on engineering while we accelerate end-to-end execution! Through the integration of domain-specific workflows and intelligent infrastructure, we deliver automated schedule tracking, resource planning, and program health visibility across the full lifecycle—from Arch/RTL handoff through silicon bring-up and productization. What you'll be doing: In this role, you will work closely with DFX software and methodology engineers, development managers, and multi-functional partners to lead methodology programs and process improvements from concept through adoption. Lead the end-to-end program lifecycle for DFX software methodology across infrastructure, implementation, verification, and bring-up — from requirements and specification through release, adoption, and continuous improvements Build and lead roadmaps, schedules, and dependencies for DFX flow, tool, and infrastructure releases, aligning methodology drops to chip program milestones through development, tapeout, fab out, and bring-up Drive the release and deployment process for DFX flows and tooling: version planning, regression and quality gates, migration paths, and user adoption across design teams Collaborate with engineering teams to define requirements and document architecture, interfaces, and workflows; participate in key design reviews and handle scope changes efficiently Coordinate license, and data infrastructure needs with CAD and IT partners so methodology programs scale with the portfolio Lead verification and validation planning for methodology — pattern coverage, regression health, and sign-off criteria — and support silicon bring-up by prioritizing lab and field debug tooling needs Proactively identify technical, resource, and schedule risks; develop mitigations in partnership with engineering, and provide clear status to leadership with recommendations that support tough trade-offs Build metrics and dashboards for methodology health, adoption, and efficiency; capture takeaways, and drive process improvement through automation What We Need To See BS in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience (advanced degree a plus) 8+ years of combined experience, built on a software engineering or computer science foundation, including a minimum of 3 years of technical program management experience Solid understanding of the ASIC/SoC design, verification, and bring-up/productization flow, and a clear understanding of where DFX fits: DFT insertion, scan/ATPG/MBIST, pattern verification, ATE and in-system test, and post-silicon debug Experience managing software, tooling, or methodology programs — release cycles, quality gates, infrastructure dependencies, and user adoption — not just implementation schedules Strong collaborative and interpersonal skills, specifically a proven track record to effectively guide and influence within a dynamic environment Deep understanding of technology and passionate about what you do, with excellent judgment, strong problem solving skills, and strong communication — written and verbal Understands and deals well with rapid development cycles and constant change; remains flexible and calm in the face of uncertainty Ways To Stand Out From The Crowd Familiarity with DFX methodologies is a strong plus Proven experience scripting and automating tasks; proficiency in Python preferred Knowledge of APIs and data analytics for program management and metrics dashboards A track record of mentorship — bringing engineers or emerging program managers up to speed on methodology and program execution 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. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence. #LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 258,750 USD for Level 4, and 200,000 USD - 322,000 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 3, 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.

We are building innovative server systems for GPU accelerated applications, such as Deep Learning. Data Center SW team architects and develops the end to end software and firmware stack for these systems. We are looking for a Senior Software Architect who has deep expertise in designing server platforms and has added understanding of application use cases in Deep Learning workloads. You will work with world class engineering teams, product management, Operations and Customer support to build systems that will truly delight our customers. What you’ll be doing: You will lead software activities for NVIDIA's deep learning server platforms, from design through production; collaborating with teams across company to deliver software solutions Drive the system architecture for a complex server platform in a multi-functional environment. Partner across application software, libraries, system software and firmware teams to design complete software solutions for new server platforms Work directly with major customers to understand their requirements and work to align their roadmap with NVIDIA’s roadmap. Work with business partners and vendors to shape their products to meet NVIDIA’s needs. Develop a roadmap of new technologies and protocols and drive their design and adoption. Mentor architects and engineering teams to grow them into future leaders. Make key technical decisions for designs involving complex inter-component dependencies. What we need to see: Deep experience in designing architecture for scalable and performant server systems, particularly at the SW/HW interface. Understanding of HPC or Deep learning workloads and use of accelerated computing platforms. Expertise in Out of Band and In-band management architectures. Knowledge of server system architecture and implications of architecture decisions on overall performance of end applications. Demonstrable experience in implementing left shift strategy to de-risk program execution. Excellent written and verbal communication skills. BS or MS degree in Computer Engineering, Computer Science, or related degree or equivalent experience. 10+ years in the area of System architecture and design. Ways to stand out from the crowd: Knowledge of cloud and cluster level deployment and management systems. Strong background of device management protocols such as Redfish, IPMI, MCTP, PLDM and RDE. Knowledge in storage and networking technologies. 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. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence. NVIDIA is 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. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you. Come, join our Data center server systems team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 3, 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.

We are building innovative server systems for GPU accelerated applications, such as Deep Learning. Data Center SW team architects and develops the end to end software and firmware stack for these systems. We are looking for a Senior Software Architect who has deep expertise in designing server platforms and has added understanding of application use cases in Deep Learning workloads. You will work with world class engineering teams, product management, Operations and Customer support to build systems that will truly delight our customers. What you’ll be doing: You will lead software activities for NVIDIA's deep learning server platforms, from design through production; collaborating with teams across company to deliver software solutions Drive the system architecture for a complex server platform in a multi-functional environment. Partner across application software, libraries, system software and firmware teams to design complete software solutions for new server platforms Work directly with major customers to understand their requirements and work to align their roadmap with NVIDIA’s roadmap. Work with business partners and vendors to shape their products to meet NVIDIA’s needs. Develop a roadmap of new technologies and protocols and drive their design and adoption. Mentor architects and engineering teams to grow them into future leaders. Make key technical decisions for designs involving complex inter-component dependencies. What we need to see: Deep experience in designing architecture for scalable and performant server systems, particularly at the SW/HW interface. Understanding of HPC or Deep learning workloads and use of accelerated computing platforms. Expertise in Out of Band and In-band management architectures. Knowledge of server system architecture and implications of architecture decisions on overall performance of end applications. Demonstrable experience in implementing left shift strategy to de-risk program execution. Excellent written and verbal communication skills. BS or MS degree in Computer Engineering, Computer Science, or related degree or equivalent experience. 10+ years in the area of System architecture and design. Ways to stand out from the crowd: Knowledge of cloud and cluster level deployment and management systems. Strong background of device management protocols such as Redfish, IPMI, MCTP, PLDM and RDE. Knowledge in storage and networking technologies. 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. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence. NVIDIA is 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. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you. Come, join our Data center server systems team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 3, 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.

We are building innovative server systems for GPU accelerated applications, such as Deep Learning. Data Center SW team architects and develops the end to end software and firmware stack for these systems. We are looking for a Senior Software Architect who has deep expertise in designing server platforms and has added understanding of application use cases in Deep Learning workloads. You will work with world class engineering teams, product management, Operations and Customer support to build systems that will truly delight our customers. What you’ll be doing: You will lead software activities for NVIDIA's deep learning server platforms, from design through production; collaborating with teams across company to deliver software solutions Drive the system architecture for a complex server platform in a multi-functional environment. Partner across application software, libraries, system software and firmware teams to design complete software solutions for new server platforms Work directly with major customers to understand their requirements and work to align their roadmap with NVIDIA’s roadmap. Work with business partners and vendors to shape their products to meet NVIDIA’s needs. Develop a roadmap of new technologies and protocols and drive their design and adoption. Mentor architects and engineering teams to grow them into future leaders. Make key technical decisions for designs involving complex inter-component dependencies. What we need to see: Deep experience in designing architecture for scalable and performant server systems, particularly at the SW/HW interface. Understanding of HPC or Deep learning workloads and use of accelerated computing platforms. Expertise in Out of Band and In-band management architectures. Knowledge of server system architecture and implications of architecture decisions on overall performance of end applications. Demonstrable experience in implementing left shift strategy to de-risk program execution. Excellent written and verbal communication skills. BS or MS degree in Computer Engineering, Computer Science, or related degree or equivalent experience. 10+ years in the area of System architecture and design. Ways to stand out from the crowd: Knowledge of cloud and cluster level deployment and management systems. Strong background of device management protocols such as Redfish, IPMI, MCTP, PLDM and RDE. Knowledge in storage and networking technologies. 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. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence. NVIDIA is 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. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you. Come, join our Data center server systems team and help build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 3, 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.